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Publications of Hau-Tieng Wu    :chronological  alphabetical  combined  bibtex listing:

Papers Published

  1. Chew, J; Hirn, M; Krishnaswamy, S; Needell, D; Perlmutter, M; Steach, H; Viswanath, S; Wu, HT, Geometric scattering on measure spaces, Applied and Computational Harmonic Analysis, vol. 70 (May, 2024) [doi]  [abs]
  2. Chung, YM; Huang, WK; Wu, HT, Topological data analysis assisted automated sleep stage scoring using airflow signals, Biomedical Signal Processing and Control, vol. 89 (March, 2024), pp. 105760-105760, Elsevier BV [doi]  [abs]
  3. Liu, T-C; Chen, Y-C; Chen, P-L; Tu, P-H; Yeh, C-H; Yeap, M-C; Wu, Y-H; Chen, C-C; Wu, H-T, Removal of electrical stimulus artifact in local field potential recorded from subthalamic nucleus by using manifold denoising., Journal of neuroscience methods, vol. 403 (March, 2024), pp. 110038 [doi]  [abs]
  4. Ding, X; Wu, HT, How do kernel-based sensor fusion algorithms behave under high-dimensional noise?, Information and Inference, vol. 13 no. 1 (March, 2024), Oxford University Press (OUP) [doi]  [abs]
  5. Chiu, N-T; Chuang, B; Anakmeteeprugsa, S; Shelley, KH; Alian, AA; Wu, H-T, Signal quality assessment of peripheral venous pressure., Journal of clinical monitoring and computing, vol. 38 no. 1 (February, 2024), pp. 101-112 [doi]  [abs]
  6. Shnitzer, T; Wu, HT; Talmon, R, Spatiotemporal analysis using Riemannian composition of diffusion operators, Applied and Computational Harmonic Analysis, vol. 68 (January, 2024) [doi]  [abs]
  7. Wang, S-C; Ting, C-K; Chen, C-Y; Liu, C; Lin, N-C; Loong, C-C; Wu, H-T; Lin, Y-T, Arterial blood pressure waveform in liver transplant surgery possesses variability of morphology reflecting recipients' acuity and predicting short term outcomes., Journal of clinical monitoring and computing, vol. 37 no. 6 (December, 2023), pp. 1521-1531 [doi]  [abs]
  8. Eid, A-M; Elgamal, M; Gonzalez-Fiol, A; Shelley, KH; Wu, H-T; Alian, AA, Using the ear photoplethysmographic waveform as an early indicator of central hypovolemia in healthy volunteers utilizing LBNP induced hypovolemia model., Physiological measurement, vol. 44 no. 5 (July, 2023) [doi]  [abs]
  9. Wu, H-T; Harezlak, J, Application of de-shape synchrosqueezing to estimate gait cadence from a single-sensor accelerometer placed in different body locations., Physiological measurement, vol. 44 no. 5 (May, 2023) [doi]  [abs]
  10. Liu, GR; Sheu, YC; Wu, HT, CENTRAL AND NONCENTRAL LIMIT THEOREMS ARISING FROM THE SCATTERING TRANSFORM AND ITS NEURAL ACTIVATION GENERALIZATION, SIAM Journal on Mathematical Analysis, vol. 55 no. 2 (April, 2023), pp. 1170-1213 [doi]  [abs]
  11. Wang, YG; Womersley, RS; Wu, HT; Yu, WH, Numerical computation of triangular complex spherical designs with small mesh ratio, Journal of Computational and Applied Mathematics, vol. 421 (March, 2023) [doi]  [abs]
  12. Ding, X; Wu, HT, Impact of Signal-to-Noise Ratio and Bandwidth on Graph Laplacian Spectrum From High-Dimensional Noisy Point Cloud, IEEE Transactions on Information Theory, vol. 69 no. 3 (March, 2023), pp. 1899-1931, Institute of Electrical and Electronics Engineers (IEEE) [doi]  [abs]
  13. Steinerberger, S; Wu, HT, Fundamental component enhancement via adaptive nonlinear activation functions, Applied and Computational Harmonic Analysis, vol. 63 (March, 2023), pp. 135-143 [doi]  [abs]
  14. Alian, A; Shelley, K; Wu, H-T, Amplitude and phase measurements from harmonic analysis may lead to new physiologic insights: lower body negative pressure photoplethysmographic waveforms as an example., Journal of clinical monitoring and computing, vol. 37 no. 1 (February, 2023), pp. 127-137 [doi]  [abs]
  15. Chen, Z; Wu, HT, Disentangling modes with crossover instantaneous frequencies by synchrosqueezed chirplet transforms, from theory to application, Applied and Computational Harmonic Analysis, vol. 62 (January, 2023), pp. 84-122 [doi]  [abs]
  16. Colominas, MA; Wu, HT, An Iterative Warping and Clustering Algorithm to Estimate Multiple Wave-Shape Functions From a Nonstationary Oscillatory Signal, IEEE Transactions on Signal Processing, vol. 71 (January, 2023), pp. 701-712, Institute of Electrical and Electronics Engineers (IEEE) [doi]  [abs]
  17. Chen, HY; Wu, HT; Chen, CY, Quality Aware Sleep Stage Classification over RIP Signals with Persistence Diagrams, 2023 IEEE 19th International Conference on Body Sensor Networks, BSN 2023 - Proceedings (January, 2023), ISBN 9798350338416 [doi]  [abs]
  18. Young, AL; van den Boom, W; Schroeder, RA; Krishnamoorthy, V; Raghunathan, K; Wu, H-T; Dunson, DB, Mutual information: Measuring nonlinear dependence in longitudinal epidemiological data., PLoS One, vol. 18 no. 4 (2023), pp. e0284904 [doi]  [abs]
  19. Shen, C; Wu, HT, Scalability and robustness of spectral embedding: landmark diffusion is all you need, Information and Inference, vol. 11 no. 4 (December, 2022), pp. 1527-1595 [doi]  [abs]
  20. Gavish, M; Su, PC; Talmon, R; Wu, HT, Optimal recovery of precision matrix for Mahalanobis distance from high-dimensional noisy observations in manifold learning, Information and Inference, vol. 11 no. 4 (December, 2022), pp. 1173-1202 [doi]  [abs]
  21. Steinerberger, S; Wu, HT, Eigenvector Phase Retrieval: Recovering eigenvectors from the absolute value of their entries, Linear Algebra and Its Applications, vol. 652 (November, 2022), pp. 239-252 [doi]  [abs]
  22. Huang, WK; Chung, YM; Wang, YB; Mandel, JE; Wu, HT, Airflow recovery from thoracic and abdominal movements using synchrosqueezing transform and locally stationary Gaussian process regression, Computational Statistics and Data Analysis, vol. 174 (October, 2022), pp. 107384-107384, Elsevier BV [doi]  [abs]
  23. Sourisseau, M; Wu, HT; Zhou, Z, ASYMPTOTIC ANALYSIS OF SYNCHROSQUEEZING TRANSFORM—TOWARD STATISTICAL INFERENCE WITH NONLINEAR-TYPE TIME-FREQUENCY ANALYSIS, Annals of Statistics, vol. 50 no. 5 (October, 2022), pp. 2694-2712 [doi]  [abs]
  24. Cheng, X; Wu, H-T, Convergence of graph Laplacian with kNN self-tuned kernels, Information and Inference: A Journal of the IMA, vol. 11 no. 3 (September, 2022), pp. 889-957, Oxford University Press (OUP) [doi]  [abs]
  25. Alian, A; Lo, YL; Shelley, K; Wu, HT, RECONSIDER PHASE RECONSTRUCTION IN SIGNALS WITH DYNAMIC PERIODICITY FROM THE MODERN SIGNAL PROCESSING PERSPECTIVE, Foundations of Data Science, vol. 4 no. 3 (September, 2022), pp. 355-393 [doi]  [abs]
  26. Zimmermann, P; Antonelli, MC; Sharma, R; Müller, A; Zelgert, C; Fabre, B; Wenzel, N; Wu, H-T; Frasch, MG; Lobmaier, SM, Prenatal stress perturbs fetal iron homeostasis in a sex specific manner., Scientific reports, vol. 12 no. 1 (June, 2022), pp. 9341 [doi]  [abs]
  27. Wu, HT; Wu, N, Strong uniform consistency with rates for kernel density estimators with general kernels on manifolds, Information and Inference, vol. 11 no. 2 (June, 2022), pp. 781-799 [doi]  [abs]
  28. Dunson, DB; Wu, HT; Wu, N, Graph based Gaussian processes on restricted domains, Journal of the Royal Statistical Society. Series B: Statistical Methodology, vol. 84 no. 2 (April, 2022), pp. 414-439 [doi]  [abs]
  29. Chiu, NT; Huwiler, S; Ferster, ML; Karlen, W; Wu, HT; Lustenberger, C, Get rid of the beat in mobile EEG applications: A framework towards automated cardiogenic artifact detection and removal in single-channel EEG, Biomedical Signal Processing and Control, vol. 72 (February, 2022) [doi]  [abs]
  30. Liu, GR; Sheu, YC; Wu, HT, Asymptotic Analysis of higher-order scattering transform of Gaussian processes, Electronic Journal of Probability, vol. 27 (January, 2022) [doi]  [abs]
  31. Shen, C; Lin, YT; Wu, HT, Robust and scalable manifold learning via landmark diffusion for long-term medical signal processing, Journal of Machine Learning Research, vol. 23 (January, 2022)  [abs]
  32. Baldazzi, G; Pani, D; Wu, HT, Extraction Algorithm for Morphologically Preserved Non-Invasive Multi-Channel Fetal ECG, Computing in Cardiology, vol. 2022-September (January, 2022), ISBN 9798350300970 [doi]  [abs]
  33. Chen, P-L; Chen, Y-C; Tu, P-H; Liu, T-C; Chen, M-C; Wu, H-T; Yeap, M-C; Yeh, C-H; Lu, C-S; Chen, C-C, Subthalamic high-beta oscillation informs the outcome of deep brain stimulation in patients with Parkinson's disease., Frontiers in human neuroscience, vol. 16 (January, 2022), pp. 958521 [doi]  [abs]
  34. Chew, J; Steach, H; Viswanath, S; Wu, HT; Hirn, M; Needell, D; Vesely, MD; Krishnaswamy, S; Perlmutter, M, THE MANIFOLD SCATTERING TRANSFORM FOR HIGH-DIMENSIONAL POINT CLOUD DATA, Proceedings of Machine Learning Research, vol. 196 (January, 2022), pp. 67-78  [abs]
  35. Chen, Z; Wu, HT, WHEN RAMANUJAN MEETS TIME-FREQUENCY ANALYSIS IN COMPLICATED TIME SERIES ANALYSIS, Pure and Applied Analysis, vol. 4 no. 4 (January, 2022), pp. 629-673 [doi]  [abs]
  36. Chen, Z; Wu, H-T, Disentangling modes with crossover instantaneous frequencies by synchrosqueezed chirplet transforms, from theory to application (December, 2021)  [abs]
  37. Steinerberger, S; Wu, H-T, Fundamental component enhancement via adaptive nonlinear activation functions (December, 2021)  [abs]
  38. Hamilton, W; Marzuola, JL; Wu, HT, On the behavior of 1-Laplacian ratio cuts on nearly rectangular domains, Information and Inference, vol. 10 no. 4 (December, 2021), pp. 1563-1610, Oxford University Press (OUP) [doi]  [abs]
  39. Ding, X; Wu, H-T, How do kernel-based sensor fusion algorithms behave under high dimensional noise? (November, 2021)  [abs]
  40. Chen, HY; Malik, J; Wu, HT; Wang, CL, Is the median hourly ambulatory heart rate range helpful in stratifying mortality risk among newly diagnosed atrial fibrillation patients?, Journal of Personalized Medicine, vol. 11 no. 11 (November, 2021) [doi]  [abs]
  41. Dunson, DB; Wu, HT; Wu, N, Spectral convergence of graph Laplacian and heat kernel reconstruction in L∞ from random samples, Applied and Computational Harmonic Analysis, vol. 55 (November, 2021), pp. 282-336 [doi]  [abs]
  42. Sourisseau, M; Wang, YG; Womersley, RS; Wu, HT; Yu, WH, Improve concentration of frequency and time (ConceFT) by novel complex spherical designs, Applied and Computational Harmonic Analysis, vol. 54 (September, 2021), pp. 137-144, Elsevier BV [doi]  [abs]
  43. Tan, C; Zhang, L; Wu, HT; Qian, T, A novel feature representation approach for single-lead heartbeat classification based on adaptive Fourier decomposition, International Journal of Wavelets, Multiresolution and Information Processing, vol. 19 no. 5 (September, 2021) [doi]  [abs]
  44. Wu, HT; Lai, TL; Haddad, GG; Muotri, A, Oscillatory Biomedical Signals: Frontiers in Mathematical Models and Statistical Analysis, Frontiers in Applied Mathematics and Statistics, vol. 7 (July, 2021) [doi]  [abs]
  45. DiPietro, JA; Raghunathan, RS; Wu, H-T; Bai, J; Watson, H; Sgambati, FP; Henderson, JL; Pien, GW, Fetal heart rate during maternal sleep., Developmental psychobiology, vol. 63 no. 5 (July, 2021), pp. 945-959 [doi]  [abs]
  46. Steinerberger, S; Wu, HT, On Zeroes of Random Polynomials and an Application to Unwinding, International Mathematics Research Notices, vol. 2021 no. 13 (July, 2021), pp. 10100-10117, Oxford University Press (OUP) [doi]  [abs]
  47. Lin, YT; Malik, J; Wu, HT, WAVE-SHAPE OSCILLATORY MODEL FOR NONSTATIONARY PERIODIC TIME SERIES ANALYSIS, Foundations of Data Science, vol. 3 no. 2 (June, 2021), pp. 99-131 [doi]  [abs]
  48. Wu, H-T; Alian, A; Shelley, K, A new approach to complicated and noisy physiological waveforms analysis: peripheral venous pressure waveform as an example., Journal of clinical monitoring and computing, vol. 35 no. 3 (May, 2021), pp. 637-653 [doi]  [abs]
  49. Liu, T-C; Liu, Y-W; Wu, H-T, Denoising click-evoked otoacoustic emission signals by optimal shrinkage., The Journal of the Acoustical Society of America, vol. 149 no. 4 (April, 2021), pp. 2659, Acoustical Society of America (ASA) [doi]  [abs]
  50. Chiu, N-T; Huwiler, S; Ferster, ML; Karlen, W; Wu, H-T; Lustenberger, C, Get rid of the beat in mobile EEG applications: A framework towards automated cardiogenic artifact detection and removal in single-channel EEG (February, 2021) [doi]  [abs]
  51. Liu, G-R; Lin, T-Y; Wu, H-T; Sheu, Y-C; Liu, C-L; Liu, W-T; Yang, M-C; Ni, Y-L; Chou, K-T; Chen, C-H; Wu, D; Lan, C-C; Chiu, K-L; Chiu, H-Y; Lo, Y-L, Large-scale assessment of consistency in sleep stage scoring rules among multiple sleep centers using an interpretable machine learning algorithm., Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine, vol. 17 no. 2 (February, 2021), pp. 159-166 [doi]  [abs]
  52. Colominas, MA; Wu, HT, Decomposing non-stationary signals with time-varying wave-shape functions, IEEE Transactions on Signal Processing, vol. 69 (January, 2021), pp. 5094-5104 [doi]  [abs]
  53. Chung, Y-M; Hu, C-S; Lo, Y-L; Wu, H-T, A Persistent Homology Approach to Heart Rate Variability Analysis With an Application to Sleep-Wake Classification., Frontiers in physiology, vol. 12 (January, 2021), pp. 637684 [doi]  [abs]
  54. Frasch, MG; Shen, C; Wu, H-T; Mueller, A; Neuhaus, E; Bernier, RA; Kamara, D; Beauchaine, TP, Brief Report: Can a Composite Heart Rate Variability Biomarker Shed New Insights About Autism Spectrum Disorder in School-Aged Children?, Journal of autism and developmental disorders, vol. 51 no. 1 (January, 2021), pp. 346-356 [doi]  [abs]
  55. Wang, H-HS; Cahill, D; Panagides, J; Nelson, CP; Wu, H-T; Estrada, C, Pattern recognition algorithm to identify detrusor overactivity on urodynamics., Neurourology and urodynamics, vol. 40 no. 1 (January, 2021), pp. 428-434 [doi]  [abs]
  56. Ding, X; Wu, HT, On the Spectral Property of Kernel-Based Sensor Fusion Algorithms of High Dimensional Data, IEEE Transactions on Information Theory, vol. 67 no. 1 (January, 2021), pp. 640-670, Institute of Electrical and Electronics Engineers (IEEE) [doi]  [abs]
  57. Meynard, A; Wu, HT, An Efficient Forecasting Approach to Reduce Boundary Effects in Real-Time Time-Frequency Analysis, IEEE Transactions on Signal Processing, vol. 69 (January, 2021), pp. 1653-1663 [doi]  [abs]
  58. Huang, Y-C; Lin, T-Y; Wu, H-T; Chang, P-J; Lo, C-Y; Wang, T-Y; Kuo, C-HS; Lin, S-M; Chung, F-T; Lin, H-C; Hsieh, M-H; Lo, Y-L, Cardiorespiratory coupling is associated with exercise capacity in patients with chronic obstructive pulmonary disease., BMC pulmonary medicine, vol. 21 no. 1 (January, 2021), pp. 22 [doi]  [abs]
  59. Liu, GR; Lo, YL; Sheu, YC; Wu, HT, Explore Intrinsic Geometry of Sleep Dynamics and Predict Sleep Stage by Unsupervised Learning Techniques, in Springer Optimization and Its Applications, vol. 168 (January, 2021), pp. 279-324 [doi]  [abs]
  60. Chen, Y-C; Wu, H-T; Tu, P-H; Yeh, C-H; Liu, T-C; Yeap, M-C; Chao, Y-P; Chen, P-L; Lu, C-S; Chen, C-C, Theta Oscillations at Subthalamic Region Predicts Hypomania State After Deep Brain Stimulation in Parkinson's Disease., Frontiers in human neuroscience, vol. 15 (January, 2021), pp. 797314 [doi]  [abs]
  61. Meynard, A; Seneviratna, G; Doyle, E; Becker, J; Wu, HT; Borg, JS, Predicting Trust Using Automated Assessment of Multivariate Interactional Synchrony, Proceedings - 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2021 (January, 2021), ISBN 9781665431767 [doi]  [abs]
  62. Malik, J; Loring, Z; Piccini, JP; Wu, H-T, Interpretable morphological features for efficient single-lead automatic ventricular ectopy detection., J Electrocardiol, vol. 65 (2021), pp. 55-63 [doi]  [abs]
  63. Su, P-C; Soliman, EZ; Wu, H-T, Robust T-End Detection via T-End Signal Quality Index and Optimal Shrinkage., Sensors (Basel, Switzerland), vol. 20 no. 24 (December, 2020), pp. E7052 [doi]  [abs]
  64. Sourisseau, M; Wang, YG; Womersley, RS; Wu, H-T; Yu, W-H, Improve Concentration of Frequency and Time (Conceft) by Novel Complex Spherical Designs (November, 2020) [doi]  [abs]
  65. Ding, X; Wu, H-T, Impact of signal-to-noise ratio and bandwidth on graph Laplacian spectrum from high-dimensional noisy point cloud (November, 2020)  [abs]
  66. Frasch, MG; Lobmaier, SM; Stampalija, T; Desplats, P; Pallarés, ME; Pastor, V; Brocco, MA; Wu, H-T; Schulkin, J; Herry, CL; Seely, AJE; Metz, GAS; Louzoun, Y; Antonelli, MC, Non-invasive biomarkers of fetal brain development reflecting prenatal stress: An integrative multi-scale multi-species perspective on data collection and analysis., Neuroscience and biobehavioral reviews, vol. 117 (October, 2020), pp. 165-183 [doi]  [abs]
  67. Wu, HT, Current state of nonlinear-type time–frequency analysis and applications to high-frequency biomedical signals, Current Opinion in Systems Biology, vol. 23 (October, 2020), pp. 8-21 [doi]  [abs]
  68. Chang, Z; Chen, Z; Stephen, CD; Schmahmann, JD; Wu, H-T; Sapiro, G; Gupta, AS, Accurate detection of cerebellar smooth pursuit eye movement abnormalities via mobile phone video and machine learning., Scientific reports, vol. 10 no. 1 (October, 2020), pp. 18641 [doi]  [abs]
  69. Chang, H-C; Wu, H-T; Huang, P-C; Ma, H-P; Lo, Y-L; Huang, Y-H, Portable Sleep Apnea Syndrome Screening and Event Detection Using Long Short-Term Memory Recurrent Neural Network., Sensors (Basel, Switzerland), vol. 20 no. 21 (October, 2020), pp. E6067 [doi]  [abs]
  70. Chang, C-H; Fang, Y-L; Wang, Y-J; Wu, H-T; Lin, Y-T, Differentiation of skin incision and laparoscopic trocar insertion via quantifying transient bradycardia measured by electrocardiogram., Journal of clinical monitoring and computing, vol. 34 no. 4 (August, 2020), pp. 753-762 [doi]  [abs]
  71. McErlean, J; Malik, J; Lin, Y-T; Talmon, R; Wu, H-T, Unsupervised Ensembling of Multiple Software Sensors with Phase Synchronization: A Robust approach For Electrocardiogram-derived Respiration (June, 2020)  [abs]
  72. Cicone, A; Wu, H-T, Convergence analysis of Adaptive Locally Iterative Filtering and SIFT method (May, 2020)  [abs]
  73. Malik, J; Soliman, EZ; Wu, H-T, An adaptive QRS detection algorithm for ultra-long-term ECG recordings., Journal of electrocardiology, vol. 60 (May, 2020), pp. 165-171 [doi]  [abs]
  74. Wang, S-C; Wu, H-T; Huang, P-H; Chang, C-H; Ting, C-K; Lin, Y-T, Novel Imaging Revealing Inner Dynamics for Cardiovascular Waveform Analysis via Unsupervised Manifold Learning., Anesthesia and analgesia, vol. 130 no. 5 (May, 2020), pp. 1244-1254 [doi]  [abs]
  75. Liu, G-R; Lustenberger, C; Lo, Y-L; Liu, W-T; Sheu, Y-C; Wu, H-T, Save Muscle Information-Unfiltered EEG Signal Helps Distinguish Sleep Stages., Sensors (Basel, Switzerland), vol. 20 no. 7 (April, 2020), pp. E2024 [doi]  [abs]
  76. Chen, Z; Wu, H-T, When Ramanujan meets time-frequency analysis in complicated time series analysis, Pure Appl. Analysis, vol. 4 (March, 2020), pp. 629-673  [abs]
  77. Liu, Y-W; Kao, S-L; Wu, H-T; Liu, T-C; Fang, T-Y; Wang, P-C, Transient-evoked otoacoustic emission signals predicting outcomes of acute sensorineural hearing loss in patients with Ménière's disease., Acta oto-laryngologica, vol. 140 no. 3 (March, 2020), pp. 230-235 [doi]  [abs]
  78. Lo, Y-L; Wu, H-T; Lin, Y-T; Kuo, H-P; Lin, T-Y, Hypoventilation patterns during bronchoscopic sedation and their clinical relevance based on capnographic and respiratory impedance analysis., Journal of clinical monitoring and computing, vol. 34 no. 1 (February, 2020), pp. 171-179 [doi]  [abs]
  79. Lobmaier, SM; Müller, A; Zelgert, C; Shen, C; Su, PC; Schmidt, G; Haller, B; Berg, G; Fabre, B; Weyrich, J; Wu, HT; Frasch, MG; Antonelli, MC, Fetal heart rate variability responsiveness to maternal stress, non-invasively detected from maternal transabdominal ECG., Archives of gynecology and obstetrics, vol. 301 no. 2 (February, 2020), pp. 405-414 [doi]  [abs]
  80. Liu, GR; Lo, YL; Malik, J; Sheu, YC; Wu, HT, Diffuse to fuse EEG spectra – Intrinsic geometry of sleep dynamics for classification, Biomedical Signal Processing and Control, vol. 55 (January, 2020) [doi]  [abs]
  81. Huroyan, V; Lerman, G; Wu, H-T, Solving Jigsaw Puzzles by the Graph Connection Laplacian, SIAM Journal on Imaging Sciences, vol. 13 no. 4 (January, 2020), pp. 1717-1753, Society for Industrial & Applied Mathematics (SIAM) [doi]
  82. Alian, A; Lo, Y-L; Shelley, K; Wu, H-T, Reconsider phase reconstruction in signals with dynamic periodicity from the modern signal processing perspective (2020) [doi]  [abs]
  83. Shen, C; Lin, Y-T; Wu, H-T, Robust and scalable manifold learning via landmark diffusion for long-term medical signal processing (2020) [doi]  [abs]
  84. Su, P-C; Miller, S; Idriss, S; Barker, P; Wu, H-T, Recovery of the fetal electrocardiogram for morphological analysis from two trans-abdominal channels via optimal shrinkage., Physiol Meas, vol. 40 no. 11 (December, 2019), pp. 115005 [doi]  [abs]
  85. Thai, DH; Wu, HT; Dunson, DB, Locally convex kernel mixtures: Bayesian subspace learning, Proceedings - 18th IEEE International Conference on Machine Learning and Applications, ICMLA 2019 (December, 2019), pp. 272-275, ISBN 9781728145495 [doi]  [abs]
  86. Talmon, R; Wu, HT, Latent common manifold learning with alternating diffusion: Analysis and applications, Applied and Computational Harmonic Analysis, vol. 47 no. 3 (November, 2019), pp. 848-892, Elsevier BV [doi]  [abs]
  87. Korolj, A; Wu, H-T; Radisic, M, A healthy dose of chaos: Using fractal frameworks for engineering higher-fidelity biomedical systems., Biomaterials, vol. 219 (October, 2019), pp. 119363 [doi]  [abs]
  88. Martinez, N; Bertran, M; Sapiro, G; Wu, HT, Non-Contact Photoplethysmogram and Instantaneous Heart Rate Estimation from Infrared Face Video, Proceedings - International Conference on Image Processing, ICIP, vol. 2019-September (September, 2019), pp. 2020-2024, ISBN 9781538662496 [doi]  [abs]
  89. Wang, YG; Womersley, RS; Wu, H-T; Yu, W-H, Numerical computation of triangular complex spherical designs with small mesh ratio (July, 2019)  [abs]
  90. Wu, H; Alagapan, S; Frohlich, F; Shin, HW, Diffusion geometry approach to efficiently remove electrical stimulation artifacts in intracranial electroencephalography, Journal of Neural Engineering, vol. 16 no. 3 (June, 2019), pp. 036010, IOP Publishing [doi]  [abs]
  91. Lu, Y; Wu, HT; Malik, J, Recycling cardiogenic artifacts in impedance pneumography, Biomedical Signal Processing and Control, vol. 51 (May, 2019), pp. 162-170 [doi]  [abs]
  92. Sourisseau, M; Wu, H-T; Zhou, Z, Asymptotic analysis of synchrosqueezing transform -- toward statistical inference with nonlinear-type time-frequency analysis (April, 2019)  [abs]
  93. Gavish, M; Talmon, R; Su, P-C; Wu, H-T, Optimal Recovery of Precision Matrix for Mahalanobis Distance from High Dimensional Noisy Observations in Manifold Learning (April, 2019)  [abs]
  94. Chen, H-Y; Pan, H-C; Chen, Y-C; Chen, Y-C; Lin, Y-H; Yang, S-H; Chen, J-L; Wu, H-T, Traditional Chinese medicine use is associated with lower end-stage renal disease and mortality rates among patients with diabetic nephropathy: a population-based cohort study., BMC complementary and alternative medicine, vol. 19 no. 1 (April, 2019), pp. 81 [doi]  [abs]
  95. Zhang, JT; Cheng, MY; Wu, HT; Zhou, B, A new test for functional one-way ANOVA with applications to ischemic heart screening, Computational Statistics and Data Analysis, vol. 132 (April, 2019), pp. 3-17, Elsevier BV [doi]  [abs]
  96. Tan, C; Zhang, L; Wu, H-T, A Novel Blaschke Unwinding Adaptive-Fourier-Decomposition-Based Signal Compression Algorithm With Application on ECG Signals., IEEE journal of biomedical and health informatics, vol. 23 no. 2 (March, 2019), pp. 672-682, Institute of Electrical and Electronics Engineers (IEEE) [doi]  [abs]
  97. Katz, O; Talmon, R; Lo, YL; Wu, HT, Alternating diffusion maps for multimodal data fusion, Information Fusion, vol. 45 (January, 2019), pp. 346-360, Elsevier BV [doi]  [abs]
  98. Shnitzer, T; Lederman, RR; Liu, GR; Talmon, R; Wu, HT, Diffusion operators for multimodal data analysis, vol. 20 (January, 2019), pp. 1-39 [doi]  [abs]
  99. Lin, Y-T; Lo, Y-L; Lin, C-Y; Frasch, MG; Wu, H-T, Unexpected sawtooth artifact in beat-to-beat pulse transit time measured from patient monitor data., PloS one, vol. 14 no. 9 (January, 2019), pp. e0221319 [doi]  [abs]
  100. Kao, SL; Lien, HW; Liu, TC; Wu, HT; Fang, TY; Wang, PC; Liu, YW, Meniere's disease prognosis by learning from transient-evoked otoacoustic emission signals, Proceedings of the International Congress on Acoustics, vol. 2019-September (January, 2019), pp. 6505-6512, ISBN 9783939296157 [doi]  [abs]
  101. Shnitzer, T; Ben-Chen, M; Guibas, L; Talmon, R; Wu, H-T, Recovering Hidden Components in Multimodal Data with Composite Diffusion Operators, SIAM Journal on Mathematics of Data Science, vol. 1 no. 3 (January, 2019), pp. 588-616, Society for Industrial & Applied Mathematics (SIAM) [doi]
  102. Malik, J; Shen, C; Wu, HT; Wu, N, CONNECTING DOTS: FROM LOCAL COVARIANCE TO EMPIRICAL INTRINSIC GEOMETRY AND LOCALLY LINEAR EMBEDDING, Pure and Applied Analysis, vol. 1 no. 4 (January, 2019), pp. 515-542 [doi]  [abs]
  103. Lin, CY; Wu, HT, Embeddings of Riemannian manifolds with finite eigenvector fields of connection Laplacian, Calculus of Variations and Partial Differential Equations, vol. 57 no. 5 (October, 2018), Springer Nature America, Inc [doi]  [abs]
  104. Escalona-Vargas, D; Wu, H-T; Frasch, MG; Eswaran, H, A Comparison of Five Algorithms for Fetal Magnetocardiography Signal Extraction., Cardiovascular engineering and technology, vol. 9 no. 3 (September, 2018), pp. 483-487, Springer Nature [doi]  [abs]
  105. Malik, J; Lo, Y-L; Wu, H-T, Sleep-wake classification via quantifying heart rate variability by convolutional neural network., Physiological measurement, vol. 39 no. 8 (August, 2018), pp. 085004, IOP Publishing [doi]  [abs]
  106. Lin, Y; Wu, H; Yang, Z; Lin, Q, Erratum: Validation of the Name Paraphlomis hispida (Lamiaceae) (Novon (2017) 25 (436-437) DOI: 10.3417/D-16-00022), Novon, vol. 26 no. 2 (August, 2018), pp. 256 [doi]  [abs]
  107. Wu, HT; Wu, JC; Huang, PC; Lin, TY; Wang, TY; Huang, YH; Lo, YL, Phenotype-based and self-learning inter-individual sleep apnea screening with a level IV-like monitoring system, Frontiers in Physiology, vol. 9 no. JUL (July, 2018), FRONTIERS MEDIA SA [doi]  [abs]
  108. Wu, H-T; Liu, Y-W, Analyzing transient-evoked otoacoustic emissions by concentration of frequency and time., The Journal of the Acoustical Society of America, vol. 144 no. 1 (July, 2018), pp. 448, Acoustical Society of America (ASA) [doi]  [abs]
  109. Lin, CY; Minasian, A; Qi, XJ; Wu, HT, Manifold Learning via the Principle Bundle Approach, Frontiers in Applied Mathematics and Statistics, vol. 4 (June, 2018) [doi]  [abs]
  110. Liu, TC; Wu, HT; Chen, YH; Fang, TY; Wang, PC; Liu, YW, Analysis of click-evoked otoacoustic emissions by concentration of frequency and time: Preliminary results from normal hearing and Ménière's disease ears, AIP Conference Proceedings, vol. 1965 (May, 2018), Author(s), ISBN 9780735416703 [doi]  [abs]
  111. Wu, H-T; Soliman, EZ, A new approach for analysis of heart rate variability and QT variability in long-term ECG recording., Biomedical engineering online, vol. 17 no. 1 (May, 2018), pp. 54 [doi]  [abs]
  112. Wu, JC; Wang, CW; Huang, YH; Wu, HT; Huang, PC; Lo, YL, A Portable Monitoring System with Automatic Event Detection for Sleep Apnea Level-IV Evaluation, Proceedings - IEEE International Symposium on Circuits and Systems, vol. 2018-May (April, 2018), ISBN 9781538648810 [doi]  [abs]
  113. Lin, CY; Su, L; Wu, HT, Wave-Shape Function Analysis: When Cepstrum Meets Time–Frequency Analysis, Journal of Fourier Analysis and Applications, vol. 24 no. 2 (April, 2018), pp. 451-505, Springer Nature [doi]  [abs]
  114. Shen, C; Frasch, MG; Wu, HT; Herry, CL; Cao, M; Desrochers, A; Fecteau, G; Burns, P, Non-invasive acquisition of fetal ECG from the maternal xyphoid process: a feasibility study in pregnant sheep and a call for open data sets., Physiological measurement, vol. 39 no. 3 (March, 2018), pp. 035005 [doi]  [abs]
  115. Wu, H; Wu, N, Think globally, fit locally under the Manifold Setup: Asymptotic Analysis of Locally Linear Embedding, edited by Hsin, T, Annals of Statistics, vol. 46 no. 6B (January, 2018), pp. 3805-3837, Institute of Mathematical Statistics [doi]  [abs]
  116. Kowalski, M; Meynard, A; Wu, HT, Convex Optimization approach to signals with fast varying instantaneous frequency, Applied and Computational Harmonic Analysis, vol. 44 no. 1 (January, 2018), pp. 89-122, Elsevier BV [doi]  [abs]
  117. Wu, H-K; Ko, Y-S; Lin, Y-S; Wu, H-T; Tsai, T-H; Chang, H-H, Corrigendum to "The correlation between pulse diagnosis and constitution identification in traditional Chinese medicine" [Complementary Ther. Med. 30 (2017) 107-112]., Complementary therapies in medicine, vol. 35 (December, 2017), pp. 145 [doi]
  118. Lin, YY; Wu, HT; Hsu, CA; Huang, PC; Huang, YH; Lo, YL, Sleep Apnea Detection Based on Thoracic and Abdominal Movement Signals of Wearable Piezoelectric Bands, IEEE Journal of Biomedical and Health Informatics, vol. 21 no. 6 (November, 2017), pp. 1533-1545, Institute of Electrical and Electronics Engineers (IEEE) [doi]  [abs]
  119. CHAO, YS; Wu, HT; Wu, CJ, Feasibility of Classifying Life Stages and Searching for the Determinants: Results from the Medical Expenditure Panel Survey 1996–2011, Frontiers in Public Health, vol. 5 (October, 2017) [doi]  [abs]
  120. Lin, T-Y; Fang, Y-F; Huang, S-H; Wang, T-Y; Kuo, C-H; Wu, H-T; Kuo, H-P; Lo, Y-L, Capnography monitoring the hypoventilation during the induction of bronchoscopic sedation: A randomized controlled trial., Scientific reports, vol. 7 no. 1 (August, 2017), pp. 8685 [doi]  [abs]
  121. Chao, Y-S; Wu, H-T; Scutari, M; Chen, T-S; Wu, C-J; Durand, M; Boivin, A, A network perspective on patient experiences and health status: the Medical Expenditure Panel Survey 2004 to 2011., BMC health services research, vol. 17 no. 1 (August, 2017), pp. 579 [doi]  [abs]
  122. Georgiou, AS; Bello-Rivas, JM; Gear, CW; Wu, HT; Chiavazzo, E; Kevrekidis, IG, An exploration algorithm for stochastic simulators driven by energy gradients, Entropy, vol. 19 no. 7 (July, 2017), pp. 294-294, MDPI AG [doi]  [abs]
  123. Malik, J; Reed, N; Wang, C-L; Wu, H-T, Single-lead f-wave extraction using diffusion geometry., Physiological measurement, vol. 38 no. 7 (June, 2017), pp. 1310-1334 [doi]  [abs]
  124. Sheu, YL; Hsu, LY; Chou, PT; Wu, HT, Entropy-based time-varying window width selection for nonlinear-type time–frequency analysis, International Journal of Data Science and Analytics, vol. 3 no. 4 (June, 2017), pp. 231-245, Springer Science and Business Media LLC [doi]  [abs]
  125. Su, L; Wu, HT, Extract Fetal ECG from Single-Lead Abdominal ECG by De-Shape Short Time Fourier Transform and Nonlocal Median, Frontiers in Applied Mathematics and Statistics, vol. 3 (February, 2017) [doi]  [abs]
  126. Herry, CL; Frasch, M; Seely, AJ; Wu, H-T, Heart beat classification from single-lead ECG using the synchrosqueezing transform., Physiological measurement, vol. 38 no. 2 (February, 2017), pp. 171-187 [doi]  [abs]
  127. Wu, H-K; Ko, Y-S; Lin, Y-S; Wu, H-T; Tsai, T-H; Chang, H-H, The correlation between pulse diagnosis and constitution identification in traditional Chinese medicine., Complementary therapies in medicine, vol. 30 (February, 2017), pp. 107-112 [doi]  [abs]
  128. Wu, HT, Embedding Riemannian manifolds by the heat kernel of the connection Laplacian, Advances in Mathematics, vol. 304 (January, 2017), pp. 1055-1079, Elsevier BV [doi]  [abs]
  129. Wu, H; Steinerberger, S; Coifman, R, Carrier frequencies, holomorphy and unwinding, SIAM Journal on Mathematical Analysis, vol. 49 no. 6 (January, 2017), pp. 4838-4864, Society for Industrial and Applied Mathematics [doi]  [abs]
  130. Li, R; Frasch, MG; Wu, H-T, Efficient Fetal-Maternal ECG Signal Separation from Two Channel Maternal Abdominal ECG via Diffusion-Based Channel Selection., Frontiers in physiology, vol. 8 (January, 2017), pp. 277 [doi]  [abs]
  131. Frasch, MG; Boylan, GB; Wu, H-T; Devane, D, Commentary: Computerised interpretation of fetal heart rate during labour (INFANT): a randomised controlled trial., Frontiers in physiology, vol. 8 (January, 2017), pp. 721 [doi]
  132. Cicone, A; Wu, H-T, How Nonlinear-Type Time-Frequency Analysis Can Help in Sensing Instantaneous Heart Rate and Instantaneous Respiratory Rate from Photoplethysmography in a Reliable Way., Frontiers in physiology, vol. 8 (January, 2017), pp. 701 [doi]  [abs]
  133. Liu, W-T; Wu, H-T; Juang, J-N; Wisniewski, A; Lee, H-C; Wu, D; Lo, Y-L, Prediction of the severity of obstructive sleep apnea by anthropometric features via support vector machine., PloS one, vol. 12 no. 5 (January, 2017), pp. e0176991 [doi]  [abs]
  134. Lin, Y-T; Wu, H-T, ConceFT for Time-Varying Heart Rate Variability Analysis as a Measure of Noxious Stimulation During General Anesthesia., IEEE transactions on bio-medical engineering, vol. 64 no. 1 (January, 2017), pp. 145-154 [doi]  [abs]
  135. Singer, A; Wu, HT, Spectral convergence of the connection Laplacian from random samples, Information and Inference, vol. 6 no. 1 (January, 2017), pp. 58-123 [doi]  [abs]
  136. Wu, C-H; Wang, T-D; Hsieh, C-H; Huang, S-H; Lin, J-W; Hsu, S-C; Wu, H-T; Wu, Y-M; Liu, T-M, Imaging Cytometry of Human Leukocytes with Third Harmonic Generation Microscopy., Scientific reports, vol. 6 no. 1 (November, 2016), pp. 37210 [doi]  [abs]
  137. Marchesini, S; Tu, YC; Wu, HT, Alternating projection, ptychographic imaging and phase synchronization, Applied and Computational Harmonic Analysis, vol. 41 no. 3 (November, 2016), pp. 815-851, Elsevier BV [doi]  [abs]
  138. Wu, H-T; Lewis, GF; Davila, MI; Daubechies, I; Porges, SW, Optimizing Estimates of Instantaneous Heart Rate from Pulse Wave Signals with the Synchrosqueezing Transform., Methods of information in medicine, vol. 55 no. 5 (October, 2016), pp. 463-472 [doi]  [abs]
  139. Lin, Y-T; Flandrin, P; Wu, H-T, When Interpolation-Induced Reflection Artifact Meets Time-Frequency Analysis., IEEE transactions on bio-medical engineering, vol. 63 no. 10 (October, 2016), pp. 2133-2141 [doi]  [abs]
  140. O'Neal, WT; Wang, YG; Wu, H-T; Zhang, Z-M; Li, Y; Tereshchenko, LG; Estes, EH; Daubechies, I; Soliman, EZ, Electrocardiographic J Wave and Cardiovascular Outcomes in the General Population (from the Atherosclerosis Risk In Communities Study)., The American journal of cardiology, vol. 118 no. 6 (September, 2016), pp. 811-815 [doi]  [abs]
  141. Chui, CK; Lin, YT; Wu, HT, Real-Time dynamics acquisition from irregular samples-With application to anesthesia evaluation, Analysis and Applications, vol. 14 no. 4 (July, 2016), pp. 537-590, World Scientific Pub Co Pte Lt [doi]  [abs]
  142. Daubechies, I; Wang, YG; Wu, H-T, ConceFT: concentration of frequency and time via a multitapered synchrosqueezed transform., Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, vol. 374 no. 2065 (April, 2016), pp. 20150193 [doi]  [abs]
  143. El Karoui, N; Wu, HT, Graph connection Laplacian methods can be made robust to noise, Annals of Statistics, vol. 44 no. 1 (February, 2016), pp. 346-372, Institute of Mathematical Statistics [doi]  [abs]
  144. Herry, CL; Cortes, M; Wu, H-T; Durosier, LD; Cao, M; Burns, P; Desrochers, A; Fecteau, G; Seely, AJE; Frasch, MG, Temporal Patterns in Sheep Fetal Heart Rate Variability Correlate to Systemic Cytokine Inflammatory Response: A Methodological Exploration of Monitoring Potential Using Complex Signals Bioinformatics., PloS one, vol. 11 no. 4 (January, 2016), pp. e0153515 [doi]  [abs]
  145. Wu, H-T; Wu, H-K; Wang, C-L; Yang, Y-L; Wu, W-H; Tsai, T-H; Chang, H-H, Modeling the Pulse Signal by Wave-Shape Function and Analyzing by Synchrosqueezing Transform., PloS one, vol. 11 no. 6 (January, 2016), pp. e0157135 [doi]  [abs]
  146. Vatter, T; Wu, HT; Chavez-Demoulin, V; Yu, B, Non-parametric estimation of intraday spot volatility: Disentangling instantaneous trend and seasonality, Econometrics, vol. 3 no. 4 (December, 2015), pp. 864-887 [doi]  [abs]
  147. Sheu, Y-L; Wu, H-T; Hsu, L-Y, Exploring laser-driven quantum phenomena from a time-frequency analysis perspective: a comprehensive study., Optics express, vol. 23 no. 23 (November, 2015), pp. 30459-30482 [doi]  [abs]
  148. Lederman, RR; Talmon, R; Wu, HT; Lo, YL; Coifman, RR, Alternating diffusion for common manifold learning with application to sleep stage assessment, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, vol. 2015-August (August, 2015), pp. 5758-5762, IEEE, ISBN 9781467369978 [doi]  [abs]
  149. Wu, H-T; Talmon, R; Lo, Y-L, Assess sleep stage by modern signal processing techniques., IEEE transactions on bio-medical engineering, vol. 62 no. 4 (April, 2015), pp. 1159-1168 [doi]  [abs]
  150. Karoui, NE; Wu, HT, Graph connection Laplacian and random matrices with random blocks, Information and Inference, vol. 4 no. 1 (March, 2015), pp. 1-42 [doi]  [abs]
  151. Wu, HT; Baudin, F; Frasch, MG; Emeriaud, G, Respiratory variability during NAVA ventilation in children: Authors' reply, Frontiers in Pediatrics, vol. 3 no. FEB (February, 2015) [doi]
  152. Wang, YG; Wu, H-T; Daubechies, I; Li, Y; Estes, EH; Soliman, EZ, Automated J wave detection from digital 12-lead electrocardiogram., Journal of electrocardiology, vol. 48 no. 1 (January, 2015), pp. 21-28 [doi]  [abs]
  153. Lederman, RR; Talmon, R; Wu, H-T; Lo, Y-L; Coifman, RR, ALTERNATING DIFFUSION FOR COMMON MANIFOLD LEARNING WITH APPLICATION TO SLEEP STAGE ASSESSMENT, 2015 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP) (2015), pp. 5758-5762
  154. Baudin, F; Wu, HT; Bordessoule, A; Beck, J; Jouvet, P; Frasch, MG; Emeriaud, G, Impact of ventilatory modes on the breathing variability in mechanically ventilated infants, Frontiers in Pediatrics, vol. 2 no. NOV (November, 2014) [doi]  [abs]
  155. Sheu, YL; Hsu, LY; Wu, HT; Li, PC; Chu, SI, A new time-frequency method to reveal quantum dynamics of atomic hydrogen in intense laser pulses: Synchrosqueezing transform, AIP Advances, vol. 4 no. 11 (November, 2014), pp. 117138-117138, AIP Publishing [doi]  [abs]
  156. Wu, H-T; Hseu, S-S; Bien, M-Y; Kou, YR; Daubechies, I, Evaluating physiological dynamics via synchrosqueezing: prediction of ventilator weaning., IEEE transactions on bio-medical engineering, vol. 61 no. 3 (March, 2014), pp. 736-744 [doi]  [abs]
  157. Wu, HT; Chan, YH; Lin, YT; Yeh, YH, Using synchrosqueezing transform to discover breathing dynamics from ECG signals, Applied and Computational Harmonic Analysis, vol. 36 no. 2 (March, 2014), pp. 354-359, Elsevier BV [doi]  [abs]
  158. Lin, Y-T; Wu, H-T; Tsao, J; Yien, H-W; Hseu, S-S, Time-varying spectral analysis revealing differential effects of sevoflurane anaesthesia: non-rhythmic-to-rhythmic ratio., Acta anaesthesiologica Scandinavica, vol. 58 no. 2 (February, 2014), pp. 157-167 [doi]  [abs]
  159. Chen, YC; Cheng, MY; Wu, HT, Non-parametric and adaptive modelling of dynamic periodicity and trend with heteroscedastic and dependent errors, Journal of the Royal Statistical Society. Series B: Statistical Methodology, vol. 76 no. 3 (January, 2014), pp. 651-682, WILEY [doi]  [abs]
  160. Marchesini, S; Schirotzek, A; Yang, C; Wu, HT; Maia, F, Augmented projections for ptychographic imaging, Inverse Problems, vol. 29 no. 11 (November, 2013), pp. 115009-115009, IOP Publishing [doi]  [abs]
  161. Zhang, J-T; Cheng, M-Y; Tseng, C-J; Wu, H-T, A New Test for One-Way ANOVA with Functional Data and Application to Ischemic Heart Screening (September, 2013)  [abs]
  162. Wu, HT, Instantaneous frequency and wave shape functions (I), Applied and Computational Harmonic Analysis, vol. 35 no. 2 (September, 2013), pp. 181-199, Elsevier BV [doi]  [abs]
  163. Thakur, G; Brevdo, E; Fučkar, NS; Wu, HT, The Synchrosqueezing algorithm for time-varying spectral analysis: Robustness properties and new paleoclimate applications, Signal Processing, vol. 93 no. 5 (May, 2013), pp. 1079-1094, Elsevier BV [doi]  [abs]
  164. Cheng, MY; Wu, HT, Local linear regression on manifolds and its geometric interpretation, Journal of the American Statistical Association, vol. 108 no. 504 (January, 2013), pp. 1421-1434, Informa UK Limited [doi]  [abs]
  165. Auger, F; Flandrin, P; Lin, YT; McLaughlin, S; Meignen, S; Oberlin, T; Wu, HT, Time-frequency reassignment and synchrosqueezing: An overview, IEEE Signal Processing Magazine, vol. 30 no. 6 (January, 2013), pp. 32-41, Institute of Electrical and Electronics Engineers (IEEE) [doi]  [abs]
  166. Wang, Y-M; Wu, H-T; Huang, E-Y; Kou, YR; Hseu, S-S, Heart rate variability is associated with survival in patients with brain metastasis: a preliminary report., BioMed research international, vol. 2013 (January, 2013), pp. 503421 [doi]  [abs]
  167. Singer, A; Wu, H-T, Two-Dimensional Tomography from Noisy Projections Taken at Unknown Random Directions., SIAM journal on imaging sciences, vol. 6 no. 1 (January, 2013), pp. 136-175 [doi]  [abs]
  168. Singer, A; Wu, H-T, Vector Diffusion Maps and the Connection Laplacian., Communications on pure and applied mathematics, vol. 65 no. 8 (August, 2012) [doi]  [abs]
  169. Thakur, G; Wu, HT, Synchrosqueezing-based recovery of instantaneous frequency from nonuniform samples, SIAM Journal on Mathematical Analysis, vol. 43 no. 5 (November, 2011), pp. 2078-2095, Society for Industrial & Applied Mathematics (SIAM) [doi]  [abs]
  170. Singer, A; Wu, H-T, Orientability and Diffusion Maps., Applied and computational harmonic analysis, vol. 31 no. 1 (July, 2011), pp. 44-58 [doi]  [abs]
  171. Wu, HT; Flandrin, P; Daubechies, I, One or two frequencies? the synchrosqueezing answers, Advances in Adaptive Data Analysis, vol. 3 no. 1-2 (April, 2011), pp. 29-39, World Scientific Pub Co Pte Lt [doi]  [abs]
  172. Daubechies, I; Lu, J; Wu, H-T, Synchrosqueezed wavelet transforms: An empirical mode decomposition-like tool, Applied and Computational Harmonic Analysis, vol. 30 no. 2 (March, 2011), pp. 243-261, Elsevier BV [doi]  [abs]

 

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