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Mathematics : Publications since January 2024

List all publications in the database.    :chronological  alphabetical  combined  bibtex listing:

Agarwal, Pankaj K.

  1. Agarwal, PK; Katz, MJ; Sharir, M, On reverse shortest paths in geometric proximity graphs, Computational Geometry: Theory and Applications, vol. 117 (February, 2024) [doi]  [abs]
  2. Agarwal, PK; Har-Peled, S, Computing Instance-Optimal Kernels in Two Dimensions, Discrete and Computational Geometry (January, 2024) [doi]  [abs]
  3. Agarwal, PK; Ezra, E, Line Intersection Searching Amid Unit Balls in 3-Space, Algorithmica (January, 2024) [doi]  [abs]

Akin, Victoria S

  1. Akin, V; Viel, S; Ellis Hagman, J; Kress, N; Tremaine, R; Fantinhardesty, K, Self-reported Student Motivations to Participate in DEI Service Work, http://sigmaa.maa.org/rume/RUME26_Proceedings2024-letter.pdf (February, 2024)  [abs]

Aquino, Wilkins

  1. Zhao, Y; Parlak, Z; Yu, W; French, D; Aquino, W; Zauscher, S, Microfluidic QCM enables ultrahigh Q-factor: a new paradigm for in-liquid gravimetric sensing., Microsystems & nanoengineering, vol. 10 no. 1 (August, 2024), pp. 116 [doi]  [abs]
  2. Aquino, W; Desmond, J; Eldred, M; Kurzawski, A; McCormick, C; Sanders, C; Smith, C; Walsh, T, Assessing decision boundaries under uncertainty, Structural and Multidisciplinary Optimization, vol. 67 no. 7 (July, 2024) [doi]  [abs]
  3. Aquino, W; Rouse, J; Bonnet, M, Active design of diffuse acoustic fields in enclosures., The Journal of the Acoustical Society of America, vol. 155 no. 2 (February, 2024), pp. 1297-1307 [doi]  [abs]

Beale, J. Thomas

  1. Beale, JT; Tlupova, S, Extrapolated regularization of nearly singular integrals on surfaces, Advances in Computational Mathematics, vol. 50 no. 4 (August, 2024) [doi]  [abs]
  2. Beale, JT; Storm, M; Tlupova, S, The adjoint double layer potential on smooth surfaces in R3 and the Neumann problem, Advances in Computational Mathematics, vol. 50 no. 3 (June, 2024) [doi]  [abs]

Bendich, Paul L

  1. Solomon, YE; Bendich, P, Convolutional persistence transforms, Journal of Applied and Computational Topology, vol. 8 no. 7 (November, 2024), pp. 1981-2013 [doi]  [abs]
  2. Catanzaro, MJ; Dharna, A; Hineman, J; Polly, JB; McGoff, K; Smith, AD; Bendich, P, Topological Decompositions Enhance Efficiency of Reinforcement Learning, IEEE Aerospace Conference Proceedings (January, 2024) [doi]  [abs]
  3. Jin, Y; McDaniel, R; Tatro, NJ; Catanzaro, MJ; Smith, AD; Bendich, P; Dwyer, MB; Fletcher, PT, Implications of data topology for deep generative models, Frontiers in Computer Science, vol. 6 (January, 2024) [doi]  [abs]

Bertozzi, Andrea L

  1. J. B. Greer and A. L. Bertozzi, H-1 solutions of a class of fourth order nonlinear equations for image processing, Discrete And Continuous Dynamical Systems, vol. 10 no. 1-2 (2004), pp. 349 -- 366

Bezemek, Zachary W

  1. Bezemek, ZW; Spiliopoulos, K, Moderate deviations for fully coupled multiscale weakly interacting particle systems, Stochastics and Partial Differential Equations: Analysis and Computations, vol. 12 no. 2 (June, 2024), pp. 1265-1373, Springer Science and Business Media LLC [doi]  [abs]

Bonolis, Dante

  1. Bonolis, D; Browning, T; Huang, Z, Density of rational points on some quadric bundle threefolds., Mathematische annalen, vol. 390 no. 3 (January, 2024), pp. 4123-4207 [doi]  [abs]
  2. Bonolis, D; Pierce, LB, Application of a polynomial sieve: Beyond separation of variables, Algebra and Number Theory, vol. 18 no. 8 (January, 2024), pp. 1515-1556 [doi]  [abs]

Brailovskaya, Tatiana I

  1. Brailovskaya, T; van Handel, R, Universality and Sharp Matrix Concentration Inequalities, Geometric and Functional Analysis, vol. 34 no. 6 (December, 2024), pp. 1734-1838 [doi]  [abs]

Bryant, Robert   (search)

  1. Buckmire, R; Beeton, B; Bryant, R; Gouvêa, FQ; Phillips, AV; Sullivan, D; Wolf, M, Michael Spivak: A Memorial, Notices of the American Mathematical Society, vol. 71 no. 6 (June, 2024), pp. 786-795 [doi]
  2. Bryant, RL, Hessianizability of surface metrics (May, 2024)
  3. Bryant, R; Florit, L; Ziller, W, Curvature homogeneous hypersurfaces in space forms (April, 2024)
  4. Bryant, R; Cheeger, J; Lima-Filho, P; Rosenberg, J; White, B, The mathematical work of H. Blaine Lawson, Jr., Pure and Applied Mathematics Quarterly, vol. 19 no. 6 (January, 2024), pp. 2627-2662, International Press
  5. Bryant, R, The generality of closed G_2 solitons, edited by Cheng, S-Y; Lima-Filho, P; Yau, SS-T; Yau, S-T, Pure and Applied Mathematics Quarterly, vol. 19 no. 6 (January, 2024), pp. 2827-2840, International Press  [abs]

Buck, Dorothy E.

  1. Tubiana, L; Alexander, GP; Barbensi, A; Buck, D; Cartwright, JHE; Chwastyk, M; Cieplak, M; Coluzza, I; Čopar, S; Craik, DJ; Di Stefano, M; Everaers, R; Faísca, PFN; Ferrari, F; Giacometti, A; Goundaroulis, D; Haglund, E; Hou, YM; Ilieva, N; Jackson, SE; Japaridze, A; Kaplan, N; Klotz, AR; Li, H; Likos, CN; Locatelli, E; López-León, T; Machon, T; Micheletti, C; Michieletto, D; Niemi, A; Niemyska, W; Niewieczerzal, S; Nitti, F; Orlandini, E; Pasquali, S; Perlinska, AP; Podgornik, R; Potestio, R; Pugno, NM; Ravnik, M; Ricca, R; Rohwer, CM; Rosa, A; Smrek, J; Souslov, A; Stasiak, A; Steer, D; Sułkowska, J; Sułkowski, P; Sumners, DWL; Svaneborg, C; Szymczak, P; Tarenzi, T; Travasso, R; Virnau, P; Vlassopoulos, D; Ziherl, P; Žumer, S, Topology in soft and biological matter, Physics Reports, vol. 1075 (July, 2024), pp. 1-137 [doi]  [abs]

Calderbank, Robert

  1. Guzel, I; Ozbayrak, D; Calderbank, R; Hareedy, A, Eliminating Media Noise While Preserving Storage Capacity: Reconfigurable Constrained Codes for Two-Dimensional Magnetic Recording, IEEE Transactions on Information Theory, vol. 70 no. 7 (July, 2024), pp. 4905-4927 [doi]  [abs]

Ciocanel, Maria-Veronica

  1. Nelson, AC; Rolls, MM; Ciocanel, M-V; McKinley, SA, Minimal Mechanisms of Microtubule Length Regulation in Living Cells., Bulletin of mathematical biology, vol. 86 no. 5 (April, 2024), pp. 58 [doi]  [abs]
  2. Ciocanel, M-V; Ding, L; Mastromatteo, L; Reichheld, S; Cabral, S; Mowry, K; Sandstede, B, Parameter Identifiability in PDE Models of Fluorescence Recovery After Photobleaching., Bulletin of mathematical biology, vol. 86 no. 4 (March, 2024), pp. 36 [doi]  [abs]

Cook, Nicholas A   (search)

  1. Cook, NA; Dembo, A, TYPICAL STRUCTURE OF SPARSE EXPONENTIAL RANDOM GRAPH MODELS, Annals of Applied Probability, vol. 34 no. 3 (June, 2024), pp. 2885-2939 [doi]  [abs]
  2. Cook, NA; Dembo, A; Pham, HT, REGULARITY METHOD AND LARGE DEVIATION PRINCIPLES FOR THE ERDŐS–RÉNYI HYPERGRAPH, Duke Mathematical Journal, vol. 173 no. 5 (April, 2024), pp. 873-946 [doi]  [abs]

Dasgupta, Samit

  1. Dasgupta, S; Kakde, M, BRUMER–STARK UNITS AND EXPLICIT CLASS FIELD THEORY, Duke Mathematical Journal, vol. 173 no. 8 (January, 2024), pp. 1477-1555 [doi]  [abs]

Daubechies, Ingrid

  1. Duprez, F; Crombin, M; Daubechies, I; Devries, N; Durant, V; El Khalil, M; Audag, N, [Update on manual bronchial clearance techniques (adults and adolescents)]., Revue des maladies respiratoires, vol. 41 no. 1 (January, 2024), pp. 43-50 [doi]  [abs]

Deng, Haohua

  1. Castor, B; Deng, H; Kerr, M; Pearlstein, G, REMARKS ON EIGENSPECTRA OF ISOLATED SINGULARITI, Pacific Journal of Mathematics, vol. 327 no. 1 (January, 2024), pp. 29-54 [doi]  [abs]

Donald, Bruce R.

  1. L. Wang and R. Mettu and B. R. Donald, An Algebraic Geometry Approach to Protein Backbone Structure Determination from NMR Data, in Proceedings of the IEEE Computational Systems Bioinformatics Conference (CSB) (2005), pp. 235--246, Stanford, CA
  2. B. R. Donald and C. Levey and C. McGray and I. Paprotny and D. Rus, A Steerable, Untethered, 250 $\times$ 60 $\mu$m MEMS Mobile Micro-Robot, in Proceedings of the 12th {\it International Symposium of Robotics Research (ISRR)} (2005), San Francisco, CA.
  3. C. Langmead and B. R. Donald, A Framework for Automated NMR Resonance Assignments and 3D Structural Homology Detection (2004), Ventura, CA ({\poster} {\it The Gordon Conference on Computational Methods in Biomolecular NMR}.)
  4. L. Wang and R. Mettu and R. Lilien and A. Yan and B. R. Donald, Exact Solutions for Internuclear Vectors and Dihedral Angles from Two RDCs and Their Application in a Systematic Search Algorithm for Determining Protein Backbone Structure (2004), Ventura, CA ({\poster} {\it The Gordon Conference on Computational Methods in Biomolecular NMR}.)
  5. Ryan H. Lilien and Mohini Sridharan and Bruce R. Donald, {Identification of Novel Small Molecule Inhibitors of Core-Binding Factor Dimerization by Computational Screening against NMR Molecular Ensembles} no. TR2004-492 (2004), Hanover, NH [pdf]
  6. B. R. Donald, Plenary lecture: Algorithmic Challenges in Structural Molecular Biology and Proteomics, in Proceedings of the Sixth International Workshop on the Algorithmic Foundations of Robotics (WAFR) (2004), pp. 1--10, University of Utrecht, Utrecht/Zeist, The Netherlands
  7. C. Langmead and B. R. Donald, High-Throughput 3D homology Detection via NMR Resonance Assignment, in Currents in Computational Molecular Biology, 2004, Eighth Annual International Conference on Research in Computational Molecular Biology (RECOMB), edited by A. Gramada and P. Bourne (2004), pp. 522, San Diego
  8. A. Yan and C. Langmead and B. R. Donald, A Probability-Based Similarity Measure for Saupe Alignment Tensors with Applications to Residual Dipolar Couplings in NMR Structural Biology, in Currents in Computational Molecular Biology, 2004, Eighth Annual International Conference on Research in Computational Molecular Biology (RECOMB), edited by A. Gramada and P. Bourne (2004), pp. 437--438, San Diego
  9. L. Wang and B. R. Donald, Analysis of a Systematic Search-Based Algorithm for Determining Protein Backbone Structure from a Minimal Number of Residual Dipolar Couplings, in Proceedings of the IEEE Computational Systems Bioinformatics Conference (CSB) (2004), pp. 319--330, Stanford, CA
  10. A. Anderson and R. Lilien and V. Popov and B. R. Donald, Ensembles of Active Site Conformations Allow Structure-Based Redesign and Drug Design (2003), New Orleans ({\poster} {\it 225th American Chemical Society National Meeting}.)
  11. Christopher J. Langmead and Bruce R. Donald, {An Improved Nuclear Vector Replacement Algorithm for Nuclear Magnetic Resonance Assignment} no. TR2004-494 (2003), Hanover, NH [pdf]
  12. B. R. Donald and C. Levey and C. McGray and D. Rus and M. Sinclair, Untethered Micro-Actuators for Autonomous Micro-robot Locomotion: Design, Fabrication, Control, and Performance, in Proceedings of the 11th {\it International Symposium of Robotics Research} (2003), Siena, Italy
  13. R. Lilien and A. Anderson and B. Donald, Modeling Protein Flexibility for Structure-Based Active Site Redesign, in Currents in Computational Molecular Biology, The Sixth Annual International Conference on Research in Computational Molecular Biology (RECOMB), edited by L. Florea and others (2002), pp. 122-123, Washington DC
  14. C. J. Langmead and B. R. Donald, Time-frequency Analysis of Protein NMR Data (2000) ({\poster} {\it The 8th Int'l Conf. on Intelligent Sys. for Mol. Biol. ({ISMB-2000})}.)
  15. C. Bailey-Kellogg and A. Widge and J. J. {Kelley III} and M. J. Berardi and J. H. Bushweller and B. R. Donald, The NOESY Jigsaw: Automated Protein Secondary Structure and Main-Chain Assignment from Sparse, Unassigned NMR Data (2000) ({\poster} {\it The 8th Int'l Conf. on Intelligent Sys. for Mol. Biol. ({ISMB-2000})}.)
  16. R. Lilien and M. Sridharan and X. Huang and J. H. Bushweller and B. R. Donald, Computational Screening Studies for Core Binding Factor Beta: Use of Multiple Conformations to Model Receptor Flexibility (2000) ({\poster} {\it The 8th Int'l Conf. on Intelligent Sys. for Mol. Biol. ({ISMB-2000})}.)
  17. C. Bailey-Kellogg and A. Widge and J. J. {Kelley III} and M. J. Berardi and J. H. Bushweller and B. R. Donald, The NOESY Jigsaw: Automated Protein Secondary Structure and Main-Chain Assignment from Sparse, Unassigned NMR Data, in The Fourth Annual International Conference on Research in Computational Molecular Biology ({RECOMB-2000}) (2000), pp. 33--44
  18. C. Bailey-Kellogg and F. Zhao and B. R. Donald, Spatial Aggregation in Scientific Data Mining, in Proceedings of the First SIAM Conference on Computational Science and Engineering (2000), Washington, DC
  19. K.-F.~B{\"o}hringer and B.~R.~Donald and N.~C.~MacDonald, {\em Programmable Vector Fields for Distributed Manipulation, with Applications to MEMS Actuator Arrays and Vibratory Parts Feeders}, International Journal of Robotics Research, vol. 18 no. 2 (1999)
  20. K.-F.~B{\"o}hringer and B.~R.~Donald and F.~Lamiraux and L.~Kavraki, Part Orientation with One or Two Stable Equilibria Using Programmable Force Fields, in IEEE International Conference on Robotics and Automation, Workshop on Distributed Manipulation (1999)
  21. K.-F. B{\"o}hringer and B. R. Donald and F. Lamiraux and L. Kavraki, Part Orientation with One or Two Stable Equilibria Using Programmable Vector Fields, in IEEE International Conference on Robotics and Automation, Workshop on Distributed Manipulation (1999), Detroit
  22. K.-F.~B{\"o}hringer and B.~R.~Donald and F.~Lamiraux and L.~Kavraki, A Single Universal Force Field Can Uniquely Pose Any Part Up To Symmetry, in 9th International Symposium of Robotics Research (ISRR) (1999)
  23. B. R. Donald and L. Gariepy and D. Rus, Experiments in Constrained Prehensile Manipulation: Distributed Manipulation with Ropes, in IEEE International Conference on Robotics and Automation, Workshop on Distributed Manipulation (1999), Detroit
  24. J.~Suh and B.~Darling and K.-F.~B{\"o}hringer and B.~R.~Donald and H.~Baltes and G.~Kovacs, CMOS Integrated Organic Ciliary Actuator Array as a General-Purpose Micromanipulation Tool, in IEEE International Conference on Robotics and Automation, Workshop on Distributed Manipulation (1999)
  25. K.-F. B{\"o}hringer and B. R. Donald, Algorithmic MEMS, in Proceedings of the 3rd International Workshop on the Algorithmic Foundations of Robotics WAFR (1998), Houston, TX
  26. A. Briggs and B. R. Donald, Robust Geometric Algorithms for Sensor Planning, in Proceedings of the International Workshop on the Algorithmic Foundations of Robotics WAFR (1996), Toulouse, France
  27. B. R. Donald and J. Jennings and D. Rus, Cooperating Autonomous Mobile Robots: Theory and Experiments (1994), MIT, Cambridge, MA (Poster, {\it NSF Design and Manufacturing Grantees Conference}.)
  28. B. R. Donald and D. Pai, The Motion of Planar Compliantly-Connected Rigid Bodies in Contact, with Applications to Automatic Fastening, International Journal of Robotics Research, vol. 12 no. 4 (1993), pp. 307--338
  29. R. Brown and P. Chew and B. R. Donald, Mobile Robots, Map-making, Shape Metrics, and Localization, in Proceedings of the International Association of Science and Technology for Development (IASTED) International Conference on Robotics and Manufacturing (1993), Oxford, England
  30. J. Jennings and D. Rus and B. R. Donald, Experimental Information Invariants for Cooperating Autonomous Mobile Robots, in Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI) Workshop on Dynamically Interacting Robots (1993), Chambery, France
  31. B. R. Donald and J. Jennings and D. Rus, Towards a Theory of Information Invariants for Cooperating Autonomous Mobile Robots, in Proceedings of the International Symposium of Robotics Research ISRR (1993), Hidden Valley, PA
  32. B. R. Donald, Robot Motion Planning, IEEE Trans. on Robotics and Automation, vol. 8 no. 2 (1992)
  33. J. Canny and B. R. Donald and G. Ressler, A Rational Rotation Method for Robust Geometric Algorithms, in Proc. ACM Symposium on Computational Geometry (1992), pp. 251--260, Berlin
  34. J. Jennings and B. R. Donald, Programming Autonomous Agents: A theory of Perceptual Equivalence, in Proceedings of the 1st AAAI Fall Symposium on Sensory Aspects of Robotic Intelligence (1991), Asilomar, CA
  35. B. R. Donald and P. Xavier, A Provably Good Approximation Algorithm for Optimal-Time Trajectory Planning, in Proc. IEEE International Conference on Robotics and Automation (1989), pp. 958--964, Scottsdale, AZ
  36. B. R. Donald, The Complexity of Planar Compliant Motion Planning with Uncertainty, in Proc. 4th ACM Symposium on Computational Geometry (1988), pp. 309--318, Urbana. IL
  37. B. R. Donald, A Theory of Error Detection and Recovery: Robot Motion Planning with Uncertainty in the Geometric Models of the Robot and Environment, in Proceedings of the International Workshop on Geometric Reasoning (1986), Oxford University, England

Dong, Conghan

  1. Dong, C; Song, A, Stability of Euclidean 3-space for the positive mass theorem, Inventiones Mathematicae, vol. 239 no. 1 (January, 2025), pp. 287-319 [doi]  [abs]
  2. Dong, C, Some stability results of positive mass theorem for uniformly asymptotically flat 3-manifolds, Annales Mathematiques du Quebec, vol. 48 no. 2 (October, 2024), pp. 427-451 [doi]  [abs]

Dunlap, Alexander J

  1. Dunlap, A; Gu, Y, Jointly stationary solutions of periodic Burgers flow, Journal of Functional Analysis, vol. 287 no. 12 (December, 2024), pp. 110656-110656, Elsevier BV [doi]  [abs]
  2. Dunlap, A; Mourrat, J-C, Sum-of-norms clustering does not separate nearby balls, Journal of Machine Learning Research, vol. 25 no. 143 (April, 2024), pp. 1-40, Microtome Publishing  [abs]

Dunson, David B.   (search)

  1. Dombowsky, A; Dunson, DB, Bayesian Clustering via Fusing of Localized Densities, Journal of the American Statistical Association (January, 2025) [doi]  [abs]
  2. Winter, S; Mahzarnia, A; Anderson, RJ; Han, ZY; Tremblay, J; Stout, JA; Moon, HS; Marcellino, D; Dunson, DB; Badea, A, Brain network fingerprints of Alzheimer's disease risk factors in mouse models with humanized APOE alleles., Magn Reson Imaging, vol. 114 (December, 2024), pp. 110251 [doi]  [abs]
  3. Zhu, Y; Peruzzi, M; Li, C; Dunson, DB, Radial neighbours for provably accurate scalable approximations of Gaussian processes, Biometrika, vol. 111 no. 4 (December, 2024), pp. 1151-1167 [doi]  [abs]
  4. Sarkar, A; Cominetti, O; Montoliu, I; Hosking, J; Pinkney, J; Martin, F-P; Dunson, DB, Bayesian semiparametric inference in longitudinal metabolomics data., Scientific reports, vol. 14 no. 1 (December, 2024), pp. 31336 [doi]  [abs]
  5. Huang, J; Morsomme, R; Dunson, D; Xu, J, Detecting changes in the transmission rate of a stochastic epidemic model., Statistics in medicine, vol. 43 no. 10 (May, 2024), pp. 1867-1882 [doi]  [abs]
  6. Chakraborty, A; Ou, R; Dunson, DB, Bayesian inference on high-dimensional multivariate binary responses., Journal of the American Statistical Association, vol. 119 no. 548 (January, 2024), pp. 2560-2571 [doi]  [abs]
  7. Melikechi, O; Dunson, DB, Ellipsoid fitting with the Cayley transform., IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society, vol. 72 (January, 2024), pp. 70-83 [doi]  [abs]
  8. Datta, J; Banerjee, S; Dunson, DB, Nonparametric Bayes multiresolution testing for high-dimensional rare events, Journal of Nonparametric Statistics (January, 2024) [doi]  [abs]
  9. Winter, S; Campbell, T; Lin, L; Srivastava, S; Dunson, DB, Emerging Directions in Bayesian Computation, Statistical Science, vol. 39 no. 1 (January, 2024), pp. 62-89 [doi]  [abs]
  10. Zhai, Q; Ye, Z; Li, C; Revie, M; Dunson, DB, Modeling Recurrent Failures on Large Directed Networks, Journal of the American Statistical Association (January, 2024) [doi]  [abs]
  11. Jin, B; Herring, AH; Dunson, D, SPATIAL PREDICTIONS ON PHYSICALLY CONSTRAINED DOMAINS: APPLICATIONS TO ARCTIC SEA SALINITY DATA, Annals of Applied Statistics, vol. 18 no. 2 (January, 2024), pp. 1596-1617 [doi]  [abs]
  12. Papamarkou, T; Skoularidou, M; Palla, K; Aitchison, L; Arbel, J; Dunson, D; Filippone, M; Fortuin, V; Hennig, P; Hernández-Lobato, JM; Hubin, A; Immer, A; Karaletsos, T; Khan, ME; Kristiadi, A; Li, Y; Mandt, S; Nemeth, C; Osborne, MA; Rudner, TGJ; Rügamer, D; Teh, YW; Welling, M; Wilson, AG; Zhang, R, Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI, Proceedings of Machine Learning Research, vol. 235 (January, 2024), pp. 39556-39586  [abs]
  13. Tang, T; Mak, S; Dunson, D, Hierarchical Shrinkage Gaussian Processes: Applications to Computer Code Emulation and Dynamical System Recovery, SIAM-ASA Journal on Uncertainty Quantification, vol. 12 no. 4 (January, 2024), pp. 1085-1112 [doi]  [abs]
  14. Chandra, NK; Dunson, DB; Xu, J, Inferring Covariance Structure from Multiple Data Sources via Subspace Factor Analysis, Journal of the American Statistical Association (January, 2024) [doi]  [abs]

Elgindi, Tarek M

  1. Elgindi, TM; Huang, Y, Regular and Singular Steady States of the 2D Incompressible Euler Equations near the Bahouri–Chemin Patch, Archive for Rational Mechanics and Analysis, vol. 249 no. 1 (February, 2025) [doi]  [abs]
  2. Elgindi, TM; Liss, K, Norm Growth, Non-uniqueness, and Anomalous Dissipation in Passive Scalars, Archive for Rational Mechanics and Analysis, vol. 248 no. 6 (December, 2024) [doi]  [abs]
  3. Drivas, TD; Elgindi, TM; Jeong, IJ, Twisting in Hamiltonian flows and perfect fluids, Inventiones Mathematicae, vol. 238 no. 1 (October, 2024), pp. 331-370 [doi]  [abs]
  4. Elgindi, TM, Remark on the stability of energy maximizers for the 2D Euler equation on $ \mathbb{T}^2 $, Communications on Pure and Applied Analysis, vol. 23 no. 10 (2024), pp. 1562-1568, American Institute of Mathematical Sciences (AIMS) [doi]

Fintzen, Jessica

  1. Fintzen, J, Supercuspidal representations in non-defining characteristics, Journal of Algebra, vol. 656 (October, 2024), pp. 196-205 [doi]  [abs]

Ge, Rong

  1. Chidambaram, M; Ge, R, ON THE LIMITATIONS OF TEMPERATURE SCALING FOR DISTRIBUTIONS WITH OVERLAPS, 12th International Conference on Learning Representations, ICLR 2024 (January, 2024)  [abs]

Getz, Jayce R.

  1. Getz, JR; Hahn, H, An introduction to automorphic representations with a view toward trace formulae, vol. 300 (January, 2024), Spinger [doi]

Goldberg, Amy

  1. Massey, DJ; Szpiech, ZA; Goldberg, A, Differentiating mechanism from outcome for ancestry-assortative mating in admixed human populations., Genetics (February, 2025), pp. iyaf022 [doi]  [abs]

Hahn, Heekyoung

  1. Getz, JR; Hahn, H, An introduction to automorphic representations with a view toward trace formulae, vol. 300 (January, 2024), Spinger [doi]

Haskins, Mark

  1. Haskins, M; Khan, I; Payne, A, Uniqueness of asymptotically conical gradient shrinking solitons in G2-Laplacian flow, Mathematische Annalen (January, 2024), Springer Science and Business Media LLC [doi]  [abs]

Herschlag, Gregory J.

  1. Preiss, D; Sperling, J; Huang, RM; Bradbury, K; Nechyba, T; Calderbank, R; Herschlag, G; Borg, JS, Where Data Science and the Disciplines Meet: Innovations in Linking Doctoral Students With Masters-Level Data Science Education, Harvard Data Science Review, vol. 6 no. 4 (August, 2024), MIT Press [doi]

Hu, Kevin

  1. Hu, Z, Suppression of Chemotactic Singularity via Viscous Flow with Large Buoyancy, SIAM Journal on Mathematical Analysis, vol. 56 no. 6 (December, 2024), pp. 7866-7902, Society for Industrial & Applied Mathematics (SIAM) [doi]
  2. Hu, Z; Luo, C; Yao, Y, Small Scale Creation for 2D Free Boundary Euler Equations with Surface Tension, Annals of PDE, vol. 10 no. 2 (December, 2024), Springer Science and Business Media LLC [doi]
  3. Hu, Z; Kiselev, A, Suppression of chemotactic blowup by strong buoyancy in Stokes-Boussinesq flow with cold boundary, Journal of Functional Analysis, vol. 287 no. 7 (October, 2024) [doi]  [abs]

Jo, Min Jun

  1. Jo, MJ; Kim, J, Quantitative asymptotic stability of the quasi-linearly stratified densities in the IPM equation with the sharp decay rates, Journal of Functional Analysis, vol. 286 no. 11 (June, 2024) [doi]  [abs]
  2. Jo, MJ; Kim, J; Lee, J, NONCONVERGENCE OF THE ROTATING STRATIFIED FLOWS TOWARD THE QUASI-GEOSTROPHIC DYNAMICS, SIAM Journal on Mathematical Analysis, vol. 56 no. 3 (January, 2024), pp. 3357-3385 [doi]  [abs]

Kiselev, Alexander A.

  1. Kiselev, A; Luo, X, The α-SQG patch problem is illposed in C2,β and W2,p, Communications on Pure and Applied Mathematics, vol. 78 no. 4 (April, 2025), pp. 742-820 [doi]  [abs]
  2. Hu, Z; Kiselev, A, Suppression of chemotactic blowup by strong buoyancy in Stokes-Boussinesq flow with cold boundary, Journal of Functional Analysis, vol. 287 no. 7 (October, 2024) [doi]  [abs]
  3. Gong, Y; Kiselev, A, CHEMOTACTIC REACTION ENHANCEMENT IN ONE DIMENSION, Communications in Mathematical Sciences, vol. 22 no. 5 (January, 2024), pp. 1287-1305 [doi]  [abs]

Levine, Adam S.

  1. Hedden, M; Levine, AS, A surgery formula for knot Floer homology, Quantum Topology, vol. 15 no. 2 (January, 2024), pp. 229-336 [doi]  [abs]

Liang, Ying

  1. Liang, Y; Zhang, H, A rigorous theory on electromagnetic diffraction by a planar aperture in a perfectly conducting screen, Journal of Mathematical Physics, vol. 65 no. 7 (July, 2024), AIP Publishing [doi]  [abs]
  2. Ito, K; Liang, Y, A Direct Probing Method of an Inverse Problem for the Eikonal Equation, SIAM Journal on Scientific Computing, vol. 46 no. 2 (April, 2024), pp. A1235-A1251, Society for Industrial & Applied Mathematics (SIAM) [doi]
  3. Li, P; Liang, Y, Stability for Inverse Source Problems of the Stochastic Helmholtz Equation with a White Noise, SIAM Journal on Applied Mathematics, vol. 84 no. 2 (April, 2024), pp. 687-709, Society for Industrial & Applied Mathematics (SIAM) [doi]

Liss, Kyle L   (search)

  1. Elgindi, TM; Liss, K, Norm Growth, Non-uniqueness, and Anomalous Dissipation in Passive Scalars, Archive for Rational Mechanics and Analysis, vol. 248 no. 6 (December, 2024) [doi]  [abs]
  2. Bedrossian, J; Liss, K, Stationary measures for stochastic differential equations with degenerate damping, Probability Theory and Related Fields, vol. 189 no. 1-2 (June, 2024), pp. 101-178 [doi]  [abs]

Liu, Jian-Guo

  1. Degond, P; Liu, J-G, Binary Particle Collisions with Mass Exchange, Journal of Statistical Physics, vol. 192 no. 2 (February, 2025), Springer Science and Business Media LLC [doi]
  2. Wang, Y; Gupta, A; Tushar, FI; Riley, B; Wang, A; Tailor, TD; Tantum, S; Liu, J-G; Bashir, MR; Lo, JY; Lafata, KJ, Concordance-based Predictive Uncertainty (CPU)-Index: Proof-of-concept with application towards improved specificity of lung cancers on low dose screening CT., Artif Intell Med, vol. 160 (February, 2025), pp. 103055, Elsevier BV [doi]  [abs]
  3. Gao, Y; Liu, JG; Liu, Z, Some Properties on the Reversibility and the Linear Response Theory of Langevin Dynamics, Acta Applicandae Mathematicae, vol. 194 no. 1 (December, 2024) [doi]  [abs]
  4. Li, L; Liu, JG; Wang, Y, Geometric ergodicity of SGLD via reflection coupling, Stochastics and Dynamics, vol. 24 no. 5 (August, 2024), World Scientific Pub Co Pte Ltd [doi]  [abs]
  5. Liu, J-G; Pego, RL, A Simple Construction of Fat Cantor Sets, The American Mathematical Monthly, vol. 131 no. 6 (July, 2024), pp. 525-525, Informa UK Limited [doi]
  6. Gao, Y; Liu, JG; Li, W, MASTER EQUATIONS FOR FINITE STATE MEAN FIELD GAMES WITH NONLINEAR ACTIVATIONS, Discrete and Continuous Dynamical Systems - Series B, vol. 29 no. 7 (July, 2024), pp. 2837-2879, American Institute of Mathematical Sciences (AIMS) [doi]  [abs] [reputed journal]
  7. Stevens, JB; Riley, BA; Je, J; Gao, Y; Wang, C; Mowery, YM; Brizel, DM; Yin, F-F; Liu, J-G; Lafata, KJ, Radiomics on spatial-temporal manifolds via Fokker-Planck dynamics., Med Phys, vol. 51 no. 5 (May, 2024), pp. 3334-3347 [doi]  [abs]
  8. Cherepanov, V; Liu, JG; Qian, Z, On the Dynamics of the Boundary Vorticity for Incompressible Viscous Flows, Journal of Scientific Computing, vol. 99 no. 2 (May, 2024) [doi]  [abs]
  9. Feng, Y; Li, L; Liu, JG; Xu, X, EXISTENCE OF WEAK SOLUTIONS TO p-NAVIER-STOKES EQUATIONS, Discrete and Continuous Dynamical Systems - Series B, vol. 29 no. 4 (April, 2024), pp. 1868-1890, American Institute of Mathematical Sciences (AIMS) [doi]  [abs] [reputed journal]
  10. Feng, Y; Li, L; Liu, JG; Tang, T, SOME GRONWALL INEQUALITIES FOR A CLASS OF DISCRETIZATIONS OF TIME FRACTIONAL EQUATIONS ON NONUNIFORM MESHES, SIAM Journal on Numerical Analysis, vol. 62 no. 5 (January, 2024), pp. 2196-2221 [doi]  [abs]
  11. Liu, JG; Witelski, T; Xu, X; Zhang, J, A Three-Dimensional Tumor Growth Model and Its Boundary Instability, Communications on Applied Mathematics and Computation (January, 2024) [doi]  [abs]

Lu, Jianfeng

  1. Triplett, L; Lu, J, Diffusion methods for generating transition paths, Journal of Computational Physics, vol. 522 (February, 2025) [doi]  [abs]
  2. Cao, Y; Lu, J, Structure-Preserving Numerical Schemes for Lindblad Equations, Journal of Scientific Computing, vol. 102 no. 1 (January, 2025) [doi]  [abs]
  3. Lu, J; Stubbs, KD, Algebraic Localization of Wannier Functions Implies Chern Triviality in Non-periodic Insulators, Annales Henri Poincare, vol. 25 no. 8 (August, 2024), pp. 3911-3926 [doi]  [abs]
  4. Bierman, J; Li, Y; Lu, J, Qubit Count Reduction by Orthogonally Constrained Orbital Optimization for Variational Quantum Excited-State Solvers., Journal of chemical theory and computation, vol. 20 no. 8 (April, 2024), pp. 3131-3143 [doi]  [abs]
  5. Loring, TA; Lu, J; Watson, AB, Locality of the windowed local density of states, Numerische Mathematik, vol. 156 no. 2 (April, 2024), pp. 741-775, Springer Science and Business Media LLC [doi]  [abs]
  6. Li, X; Pura, J; Allen, A; Owzar, K; Lu, J; Harms, M; Xie, J, DYNATE: Localizing rare-variant association regions via multiple testing embedded in an aggregation tree., Genet Epidemiol, vol. 48 no. 1 (February, 2024), pp. 42-55 [doi]  [abs]
  7. Chen, C; Chen, Z; Lu, J, REPRESENTATION THEOREM FOR MULTIVARIABLE TOTALLY SYMMETRIC FUNCTIONS*, Communications in Mathematical Sciences, vol. 22 no. 5 (January, 2024), pp. 1195-1201 [doi]  [abs]
  8. Jing, Y; Chen, J; Li, L; Lu, J, A Machine Learning Framework for Geodesics Under Spherical Wasserstein–Fisher–Rao Metric and Its Application for Weighted Sample Generation, Journal of Scientific Computing, vol. 98 no. 1 (January, 2024) [doi]  [abs]
  9. Chen, Z; Lu, J; Lu, Y; Zhang, X, ON THE CONVERGENCE OF SOBOLEV GRADIENT FLOW FOR THE GROSS-PITAEVSKII EIGENVALUE PROBLEM, SIAM Journal on Numerical Analysis, vol. 62 no. 2 (January, 2024), pp. 667-691, Society for Industrial & Applied Mathematics (SIAM) [doi]  [abs]
  10. Cheng, X; Lu, J; Tan, Y; Xie, Y, Convergence of Flow-Based Generative Models via Proximal Gradient Descent in Wasserstein Space, IEEE Transactions on Information Theory, vol. 70 no. 11 (January, 2024), pp. 8087-8106 [doi]  [abs]
  11. He, Y; Balasubramanian, K; Sriperumbudur, BK; Lu, J, Regularized Stein Variational Gradient Flow, Foundations of Computational Mathematics (January, 2024) [doi]  [abs]
  12. Lu, J; Otto, F; Wang, L, Optimal artificial boundary conditions based on second-order correctors for three dimensional random elliptic media, Communications in Partial Differential Equations, vol. 49 no. 7-8 (January, 2024), pp. 609-670 [doi]  [abs]
  13. Chen, Z; Lu, J; Zhang, A, ONE-DIMENSIONAL TENSOR NETWORK RECOVERY, SIAM Journal on Matrix Analysis and Applications, vol. 45 no. 3 (January, 2024), pp. 1217-1244 [doi]  [abs]
  14. Zhang, S; Lu, J; Zhao, H, Deep Network Approximation: Beyond ReLU to Diverse Activation Functions, JOURNAL OF MACHINE LEARNING RESEARCH, vol. 25 (2024)

Maggioni, Mauro

  1. E Causevic and R~R Coifman and R Isenhart and A Jacquin and E~R John and M Maggioni and L~S Prichep and F~J Warner, QEEG-based classification with wavelet packets and microstate features for triage applications in the ER (2005)
  2. GL Davis and Mauro Maggioni and FJ Warner and FB Geshwind and AC Coppi and RA DeVerse and RR Coifman, Hyper-spectral Analysis of normal and malignant colon tissue microarray sections using a novel DMD system (2004) (Poster, Optical Imaging NIH workshop, to app. in proc..)
  3. Ronald R Coifman and Mauro Maggioni, Multiresolution Analysis associated to diffusion semigroups: construction and fast algorithms no. YALE/DCS/TR-1289 (2004)

Mattingly, Jonathan C.   (search)

  1. Earle, G; Mattingly, JC, Convergence of stratified MCMC sampling of non-reversible dynamics, Stochastics and Partial Differential Equations: Analysis and Computations, vol. 12 no. 4 (December, 2024), pp. 2289-2329 [doi]  [abs]
  2. Agazzi, A; Grotto, F; Mattingly, JC, Random splitting of point vortex flows, Electronic Communications in Probability, vol. 29 (January, 2024) [doi]  [abs]

Mukherjee, Sayan

  1. Mukherjee, S; Roy, S, Regularized Bayesian best response learning in finite games, Games and Economic Behavior, vol. 149 (January, 2025), pp. 1-31 [doi]  [abs]
  2. Kirveslahti, H; Mukherjee, S, Representing fields without correspondences: the lifted Euler characteristic transform, Journal of Applied and Computational Topology, vol. 8 no. 1 (March, 2024), pp. 1-34 [doi]  [abs]
  3. Patel, N; Paul, CK; Kar, IN; Mukherjee, S, Finite Time Adaptive Backstepping Control Approach for Quadrotors, IFAC-PapersOnLine, vol. 57 (March, 2024), pp. 125-130 [doi]  [abs]
  4. Arya, S; Curry, J; Mukherjee, S, A Sheaf-Theoretic Construction of Shape Space, Foundations of Computational Mathematics (January, 2024) [doi]  [abs]
  5. Roldan-Roa, E; Roldan-Roa, ÉB; Raave, DK; van Herwegen, J; Polytimou, N; Mukherjee, S; Colasante, T; Malti, T; Mori, J, Play My Math: Second Development Cycle of an EdTech Tool Supporting the Teaching and Learning of Fractions Through Music in Algebraic Notation, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14786 LNCS (January, 2024), pp. 44-53 [doi]  [abs]
  6. Roldan-Roa, E; Roldan-Roa, ÉB; Raave, DK; Van Herwegen, J; Politimou, N; Mukherjee, S; Colasante, T; Malti, T; Mori, J; Specht, M, Play My Math: First Development Cycle of an EdTech Tool Supporting the Teaching and Learning of Fractions Through Music in Algebraic Notation, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 15160 LNCS (January, 2024), pp. 241-246 [doi]  [abs]
  7. Mukherjee, S; Roy, S, PERTURBED BAYESIAN BEST RESPONSE DYNAMIC IN CONTINUUM GAMES, SIAM Journal on Control and Optimization, vol. 62 no. 6 (January, 2024), pp. 3091-3120 [doi]  [abs]

Nelson, Anna C

  1. Nelson, AC; Rolls, MM; Ciocanel, M-V; McKinley, SA, Minimal Mechanisms of Microtubule Length Regulation in Living Cells., Bulletin of mathematical biology, vol. 86 no. 5 (April, 2024), pp. 58, Springer Science and Business Media LLC [doi]  [abs]
  2. Kent, A; Leiderman, K; Nelson, AC; Sindi, SS; Stadt, MM; Xiong, L; Zhang, Y, Studying the Effects of Oral Contraceptives on Coagulation Using a Mathematical Modeling Approach, in The IMA Volumes in Mathematics and its Applications (2024), pp. 83-132, Springer Nature Switzerland, ISBN 9783031585159 [doi]  [abs]

Ng, Lenhard L.

  1. Feehan, PMN; Ng, LL; Ozsváth, PS, Frontiers in Geometry and Topology (July, 2024), pp. 320 pages, American Mathematical Society, ISBN 9781470470876  [abs]

Nolen, James H.

  1. Iyer, G; Lu, E; Nolen, J, USING BERNOULLI MAPS TO ACCELERATE MIXING OF A RANDOM WALK ON THE TORUS, Quarterly of Applied Mathematics, vol. 82 no. 2 (January, 2024), pp. 359-390, American Mathematical Society (AMS) [doi]  [abs]

Pierce, Lillian B.

  1. Browning, T; Pierce, LB; Schindler, D, GENERALISED QUADRATIC FORMS OVER TOTALLY REAL NUMBER FIELDS, Journal of the Institute of Mathematics of Jussieu, vol. 23 no. 6 (November, 2024), pp. 2859-2912 [doi]  [abs]
  2. Anderson, TC; Maldague, D; Pierce, LB; Yung, PL, On Polynomial Carleson Operators Along Quadratic Hypersurfaces, Journal of Geometric Analysis, vol. 34 no. 10 (October, 2024) [doi]  [abs]
  3. Gressman, PT; Pierce, LB; Roos, J; Yung, PL, A NEW TYPE OF SUPERORTHOGONALITY, Proceedings of the American Mathematical Society, vol. 152 no. 2 (February, 2024), pp. 665-675 [doi]  [abs]
  4. Bonolis, D; Pierce, LB, Application of a polynomial sieve: Beyond separation of variables, Algebra and Number Theory, vol. 18 no. 8 (January, 2024), pp. 1515-1556 [doi]  [abs]

Randles, Amanda

  1. Feiger, B; Jensen, CW; Bryner, BS; Segars, WP; Randles, A, Modeling the effect of patient size on cerebral perfusion during veno-arterial extracorporeal membrane oxygenation., Perfusion, vol. 39 no. 7 (October, 2024), pp. 1295-1303 [doi]  [abs]
  2. Tanade, C; Khan, NS; Rakestraw, E; Ladd, WD; Draeger, EW; Randles, A, Establishing the longitudinal hemodynamic mapping framework for wearable-driven coronary digital twins., NPJ digital medicine, vol. 7 no. 1 (September, 2024), pp. 236, Springer Science and Business Media LLC [doi]  [abs]
  3. Chidyagwai, SG; Kaplan, MS; Jensen, CW; Chen, JS; Chamberlain, RC; Hill, KD; Barker, PCA; Slesnick, TC; Randles, A, Surgical Modulation of Pulmonary Artery Shear Stress: A Patient-Specific CFD Analysis of the Norwood Procedure., Cardiovasc Eng Technol, vol. 15 no. 4 (August, 2024), pp. 431-442 [doi]  [abs]
  4. Geddes, J; Randles, A; Tanade, C; Ladd, W; Khan, NS, Velocity Temporal Shape Affects Simulated Flow in Left Coronary Arteries (July, 2024)
  5. Vardhan, M; Tanade, C; Chen, SJ; Mahmood, O; Chakravartti, J; Jones, WS; Kahn, AM; Vemulapalli, S; Patel, M; Leopold, JA; Randles, A, Diagnostic Performance of Coronary Angiography Derived Computational Fractional Flow Reserve., J Am Heart Assoc, vol. 13 no. 13 (July, 2024), pp. e029941 [doi]  [abs]
  6. Seidel, E; Randles, A; Arthur, R; Bergman, K; Carlson, B; Deelman, E; Grout, R; Hendrickson, B; Reed, D, 2024 Advanced Scientific Computing Advisory Committee (ASCR) Facilities Subcommittee Recommendations (May, 2024), USDOE Office of Science (SC) [doi]
  7. Geddes, JR; Randles, A, Optimizing Temporal Waveform Analysis: A Novel Pipeline for Efficient Characterization of Left Coronary Artery Velocity Profiles., ArXiv (February, 2024)  [abs]

Reed, Michael C.

  1. Best, J; Kim, R; Reed, M; Nijhout, HF, A mathematical model of melatonin synthesis and interactions with the circadian clock., Mathematical biosciences, vol. 377 (November, 2024), pp. 109280 [doi]  [abs]
  2. Mena, S; Cruikshank, A; Best, J; Nijhout, HF; Reed, MC; Hashemi, P, Modulation of serotonin transporter expression by escitalopram under inflammation., Communications biology, vol. 7 no. 1 (June, 2024), pp. 710 [doi]  [abs]
  3. Buchanan, AM; Mena, S; Choukari, I; Vasa, A; Crawford, JN; Fadel, J; Maxwell, N; Reagan, L; Cruikshank, A; Best, J; Nijhout, HF; Reed, M; Hashemi, P, Serotonin as a biomarker of toxin-induced Parkinsonism., Molecular medicine (Cambridge, Mass.), vol. 30 no. 1 (March, 2024), pp. 33 [doi]  [abs]
  4. Cruikshank, A; Reed, MC; Frederik Nijhout, H, Sex differences in glutathione metabolism and acetaminophen toxicity, Metabolism and Target Organ Damage, vol. 4 no. 2 (January, 2024) [doi]  [abs]
  5. Suzuki, A; Henao, R; Reed, MC; Nijhout, HF; Tripathi, M; Singh, BK; Yen, PM; Diehl, AM; Abdelmalek, MF, Lower hepatic CBS and PEMT expression in advanced NAFLD: inferencing strategies to lower homocysteine with a mathematical model, Metabolism and Target Organ Damage, vol. 4 no. 3 (January, 2024) [doi]  [abs]
  6. Duncan, W; Antoneli, F; Best, J; Golubitsky, M; Jin, J; Nijhout, HF; Reed, M; Stewart, I, Homeostasis Patterns, SIAM Journal on Applied Dynamical Systems, vol. 23 no. 3 (January, 2024), pp. 2262-2292 [doi]  [abs]

Rossman, Benjamin

  1. Rossman, B, Formula Size-Depth Tradeoffs for Iterated Sub-permutation Matrix Multiplication, Proceedings of the Annual ACM Symposium on Theory of Computing (June, 2024), pp. 1386-1395 [doi]  [abs]

Rudin, Cynthia D.

  1. Zhang, H; Mahabadi, RK; Rudin, C; Guilleminot, J; Brinson, LC, Uncertainty quantification of acoustic metamaterial bandgaps with stochastic material properties and geometric defects, Computers and Structures, vol. 305 (December, 2024) [doi]  [abs]
  2. Chen, SF; Guo, Z; Ding, C; Hu, X; Rudin, C, Sparse learned kernels for interpretable and efficient medical time series processing, Nature Machine Intelligence, vol. 6 no. 10 (October, 2024), pp. 1132-1144 [doi]  [abs]
  3. Semenova, L; Wang, Y; Falcinelli, S; Archin, N; Cooper-Volkheimer, AD; Margolis, DM; Goonetilleke, N; Murdoch, DM; Rudin, CD; Browne, EP, Machine learning approaches identify immunologic signatures of total and intact HIV DNA during long-term antiretroviral therapy., Elife, vol. 13 (September, 2024) [doi]  [abs]
  4. Hahn, S; Yin, J; Zhu, R; Xu, W; Jiang, Y; Mak, S; Rudin, C, SentHYMNent: An Interpretable and Sentiment-Driven Model for Algorithmic Melody Harmonization, Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (August, 2024), pp. 5050-5060 [doi]  [abs]
  5. Ding, C; Guo, Z; Chen, Z; Lee, RJ; Rudin, C; Hu, X, SiamQuality: a ConvNet-based foundation model for photoplethysmography signals., Physiological measurement, vol. 45 no. 8 (August, 2024) [doi]  [abs]
  6. Parikh, H; Sun, H; Amerineni, R; Rosenthal, ES; Volfovsky, A; Rudin, C; Westover, MB; Zafar, SF, How many patients do you need? Investigating trial designs for anti-seizure treatment in acute brain injury patients., Annals of clinical and translational neurology, vol. 11 no. 7 (July, 2024), pp. 1681-1690 [doi]  [abs]
  7. Bravo, F; Rudin, C; Shaposhnik, Y; Yuan, Y, Interpretable Prediction Rules for Congestion Risk in Intensive Care Units, Stochastic Systems, vol. 14 no. 2 (June, 2024), pp. 111-130 [doi]  [abs]
  8. Ashokkumar, M; Mei, W; Peterson, JJ; Harigaya, Y; Murdoch, DM; Margolis, DM; Kornfein, C; Oesterling, A; Guo, Z; Rudin, CD; Jiang, Y; Browne, EP, Integrated Single-cell Multiomic Analysis of HIV Latency Reversal Reveals Novel Regulators of Viral Reactivation., Genomics Proteomics Bioinformatics, vol. 22 no. 1 (May, 2024) [doi]  [abs]
  9. Ding, C; Guo, Z; Rudin, C; Xiao, R; Shah, A; Do, DH; Lee, RJ; Clifford, G; Nahab, FB; Hu, X, Learning From Alarms: A Robust Learning Approach for Accurate Photoplethysmography-Based Atrial Fibrillation Detection Using Eight Million Samples Labeled With Imprecise Arrhythmia Alarms., IEEE journal of biomedical and health informatics, vol. 28 no. 5 (May, 2024), pp. 2650-2661 [doi]  [abs]
  10. Zhang, R; Xin, R; Seltzer, M; Rudin, C, Optimal Sparse Survival Trees., Proceedings of machine learning research, vol. 238 (May, 2024), pp. 352-360  [abs]
  11. Seale-Carlisle, T; Jain, S; Lee, C; Levenson, C; Ramprasad, S; Garrett, B; Roy, S; Rudin, C; Volfovsky, A, Evaluating Pre-trial Programs Using Interpretable Machine Learning Matching Algorithms for Causal Inference, Proceedings of the AAAI Conference on Artificial Intelligence, vol. 38 no. 20 (March, 2024), pp. 22331-22340 [doi]  [abs]
  12. Donnelly, J; Moffett, L; Barnett, AJ; Trivedi, H; Schwartz, F; Lo, J; Rudin, C, AsymMirai: Interpretable Mammography-based Deep Learning Model for 1-5-year Breast Cancer Risk Prediction., Radiology, vol. 310 no. 3 (March, 2024), pp. e232780 [doi]  [abs]
  13. Sun, Y; Chen, Z; Orlandi, V; Wang, T; Rudin, C, Sparse and Faithful Explanations Without Sparse Models, Proceedings of Machine Learning Research, vol. 238 (January, 2024), pp. 2071-2079  [abs]
  14. Katta, S; Parikh, H; Rudin, C; Volfovsky, A, Interpretable Causal Inference for Analyzing Wearable, Sensor, and Distributional Data, Proceedings of Machine Learning Research, vol. 238 (January, 2024), pp. 3340-3348  [abs]
  15. Parikh, H; Lanners, Q; Akras, Z; Zafar, SF; Westover, MB; Rudin, C; Volfovsky, A, Safe and Interpretable Estimation of Optimal Treatment Regimes, Proceedings of Machine Learning Research, vol. 238 (January, 2024), pp. 2134-2142  [abs]
  16. Rudin, C; Zhong, C; Semenova, L; Seltzer, M; Parr, R; Liu, J; Katta, S; Donnelly, J; Chen, H; Boner, Z, Position: Amazing Things Come From Having Many Good Models, Proceedings of Machine Learning Research, vol. 235 (January, 2024), pp. 42783-42795  [abs]
  17. Yang, J; Barnett, AJ; Donnelly, J; Kishore, S; Fang, J; Schwartz, FR; Chen, C; Lo, JY; Rudin, C, FPN-IAIA-BL: A Multi-Scale Interpretable Deep Learning Model for Classification of Mass Margins in Digital Mammography, IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (January, 2024), pp. 5003-5009 [doi]  [abs]
  18. Mahabadi, RK; Chen, Z; Daraio, C; Rudin, C; Brinson, LC, A robust framework for the generation of random metamaterials based on a graph algorithm, Proceedings of SPIE - The International Society for Optical Engineering, vol. 13109 (January, 2024) [doi]  [abs]
  19. Garrett, BL; Rudin, C, The Right to a Glass Box: Rethinking the Use of Artificial Intelligence in Criminal Justice, Cornell Law Review, vol. 109 no. 3 (2024), pp. 561-627

Ryser, Marc D.

  1. Nguyen, DL; Shelley Hwang, E; Ryser, MD; Grimm, LJ, Imaging Changes and Outcomes of Patients Undergoing Active Monitoring for Ductal Carcinoma In Situ: Seven-Year Follow-up Study., Acad Radiol, vol. 31 no. 7 (July, 2024), pp. 2654-2662 [doi]  [abs]
  2. Iyer, M; Mallo, D; Maley, CC; Fortunato, A; Cisneros, L; King, LM; Ryser, MD; Lo, JY; Hall, A; Marks, JR; Hwang, S, Abstract A038: Evaluating DCIS progression: A comparative analysis of CNA predictive power derived from lpWGS and WES data, Cancer Research, vol. 84 no. 3_Supplement_2 (February, 2024), pp. A038-A038, American Association for Cancer Research (AACR) [doi]  [abs]
  3. Liu, X; Ren, Y; Ryser, M; Grimm, LJ; Lo, JY, A Residual-Attention Multimodal Fusion Network (ResAMF-Net) for Detection and Classification of Breast Cancer, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 12927 (January, 2024), ISBN 9781510671584 [doi]  [abs]

Sapiro, Guillermo

  1. Gianneschi, JR; Washington, KA; Nicholas, J; Pilato, I; LeMay-Russell, S; Rivera-Cancel, AM; Mines, EV; Jackson, JE; Marsan, S; Lachman, S; Kim, YK; Di Martino, JM; Pendergast, J; Loeb, KL; Katzman, DK; Marcus, MD; Bryant-Waugh, R; Sapiro, G; Zucker, NL, Assessing Fears of Negative Consequences in Children With Symptoms of Avoidant Restrictive Food Intake Disorder., Int J Eat Disord, vol. 57 no. 12 (December, 2024), pp. 2329-2340 [doi]  [abs]
  2. Aikat, V; Krishnappa Babu, PR; Carpenter, KLH; Di Martino, JM; Espinosa, S; Davis, N; Franz, L; Spanos, M; Dawson, G; Sapiro, G, Digital Phenotyping based on a Mobile App Identifies Distinct and Overlapping Features in Children Diagnosed with Autism versus ADHD, UIST Adjunct 2024 - Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology (October, 2024) [doi]  [abs]
  3. Schlesinger, O; Kundu, R; Isaev, D; Choi, JY; Goetz, SM; Turner, DA; Sapiro, G; Peterchev, AV; Di Martino, JM, Scalp surface estimation and head registration using sparse sampling and 3D statistical models., Comput Biol Med, vol. 178 (August, 2024), pp. 108689 [doi]  [abs]
  4. Isaev, DY; Sabatos-DeVito, M; Di Martino, JM; Carpenter, K; Aiello, R; Compton, S; Davis, N; Franz, L; Sullivan, C; Dawson, G; Sapiro, G, Computer Vision Analysis of Caregiver-Child Interactions in Children with Neurodevelopmental Disorders: A Preliminary Report., J Autism Dev Disord, vol. 54 no. 6 (June, 2024), pp. 2286-2297 [doi]  [abs]
  5. Krishnappa Babu, PR; Di Martino, JM; Carpenter, KLH; Compton, S; Davis, N; Eichner, B; Espinosa, S; Franz, L; Perochon, S; Dawson, G; Sapiro, G, Large-scale Validation of a Scalable and Portable Behavioral Digital Screening Tool for Autism at Home, Conference on Human Factors in Computing Systems - Proceedings (May, 2024) [doi]  [abs]
  6. Isaev, DY; Vlasova, RM; Di Martino, JM; Stephen, CD; Schmahmann, JD; Sapiro, G; Gupta, AS, Uncertainty of Vowel Predictions as a Digital Biomarker for Ataxic Dysarthria., Cerebellum (London, England), vol. 23 no. 2 (April, 2024), pp. 459-470 [doi]  [abs]
  7. Goldberg, CB; Adams, L; Blumenthal, D; Brennan, PF; Brown, N; Butte, AJ; Cheatham, M; deBronkart, D; Dixon, J; Drazen, J; Evans, BJ; Hoffman, SM; Holmes, C; Lee, P; Manrai, AK; Omenn, GS; Perlin, JB; Ramoni, R; Sapiro, G; Sarkar, R; Sood, H; Vayena, E; Kohane, IS; RAISE Consortium, To do no harm - and the most good - with AI in health care., Nature medicine, vol. 30 no. 3 (March, 2024), pp. 623-627 [doi]
  8. Gil, NM; Bertran, M; Sapiro, G, Achieving Group Distributional Robustness and Minimax Group Fairness with Interpolating Classifiers, Proceedings of Machine Learning Research, vol. 238 (January, 2024), pp. 2629-2637  [abs]
  9. Farzam, A; Tannenbaum, A; Sapiro, G, From Geometry to Causality-Ricci Curvature and the Reliability of Causal Inference on Networks, Proceedings of Machine Learning Research, vol. 235 (January, 2024), pp. 13086-13108  [abs]
  10. Huang, L; Qiu, Q; Sapiro, G, PQ-VAE: Learning Hierarchical Discrete Representations with Progressive Quantization, IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (January, 2024), pp. 7550-7558 [doi]  [abs]
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