Math @ Duke

Papers Published
 Salazar, M; Paccagnan, D; Agazzi, A; Heemels, WPMH, Urgencyaware optimal routing in repeated games through artificial currencies,
European Journal of Control
(January, 2021) [doi] [abs]
 AGAZZI, A; MATTINGLY, JC, SEEMINGLY STABLE CHEMICAL KINETICS CAN BE STABLE, MARGINALLY STABLE, OR UNSTABLE,
Communications in Mathematical Sciences, vol. 18 no. 6
(January, 2020),
pp. 16051642, International Press of Boston [doi] [abs]
 Agazzi, A; Lu, J, Global optimality of softmax policy gradient with single hidden layer neural networks in the meanfield regime.,
Corr, vol. abs/2010.11858
(2020)
 Li, L; Krznar, P; Erban, A; Agazzi, A; MartinLevilain, J; Supale, S; Kopka, J; Zamboni, N; Maechler, P, Metabolomics Identifies a Biomarker Revealing In Vivo Loss of Functional βCell Mass Before Diabetes Onset.,
Diabetes, vol. 68 no. 12
(December, 2019),
pp. 22722286 [doi] [abs]
 Agazzi, A; Lu, J, Temporaldifference learning for nonlinear value function approximation in the lazy training regime.,
Corr, vol. abs/1905.10917
(2019)
 Agazzi, A; Dembo, A; Eckmann, JP, On the Geometry of Chemical Reaction Networks: Lyapunov Function and Large Deviations,
Journal of Statistical Physics, vol. 172 no. 2
(July, 2018),
pp. 321352 [doi] [abs]
 Agazzi, A; Dembo, A; Eckmann, JP, Large deviations theory for markov jump models of chemical reaction networks,
The Annals of Applied Probability, vol. 28 no. 3
(June, 2018),
pp. 18211855 [doi] [abs]
 Agazzi, A; Eckmann, JP; Graf, GM, The Colored Hofstadter Butterfly for the Honeycomb Lattice,
Journal of Statistical Physics, vol. 156 no. 3
(January, 2014),
pp. 417426 [doi] [abs]


dept@math.duke.edu
ph: 919.660.2800
fax: 919.660.2821
 
Mathematics Department
Duke University, Box 90320
Durham, NC 277080320

