Metastability for systems of interacting neurons
Author:
Affiliation:
1. SAMM, Statistique, Analyse et Modélisation Multidisciplinaire, Université Paris 1 Panthéon-Sorbonne, EA 4543 et FR FP2M 2036 CNRS, Paris, France
2. LJLL-UMR 7598, Sorbonne Université, Paris, France
Publisher
Institute of Mathematical Statistics
Subject
Statistics, Probability and Uncertainty,Statistics and Probability
Reference28 articles.
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2. M. André and L. Planche. The effect of graph connectivity on metastability in a stochastic system of spiking neurons. Stochastic Process. Appl. 131 (2021) 292–310.
3. N. Berglund. Kramers’ law: Validity, derivations and generalisations. Markov Process. Related Fields 19 (2013) 469–490.
4. A. Bianchi, A. Gaudillière and P. Milanesi. On soft capacities, quasi-stationary distributions and the pathwise approach to metastability. J. Stat. Phys. 181 (2020) 1052–1086.
5. A. Bovier and F. Den Hollander. Metastability. A Potential-Theoretic Approach. Grundlagen der Mathematischen Wissenschaften, Springer Series 351, 2015.
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