Fixed-kinetic Neural Hamiltonian Flows for enhanced interpretability and reduced complexity
V. Souveton, A. Guillin, J. Jasche, G. Lavaux and M. Michel
arXiv preprint arXiv:2302.01955.
Law of large numbers and central limit theorem for wide two-layer neural networks: the mini-batch and noisy case
A. Descours, A. Guillin, M. Michel and B. Nectoux
arXiv preprint arXiv:2207.12734.
Journal papers
PDMP characterisation of event-chain Monte Carlo algorithms for particle systems
A. Monemvassitis, A. Guillin and M. Michel,
Journal of Statistical Physics 190, 66 (2023).
Loop-Cluster Monte Carlo Algorithm for Classical Statistical Models
L. Zhang, M. Michel, E. M. Elçi and Y. Deng,
Physical Review Letters 125 (20), 200603 (2020).
Forward Event-chain Monte Carlo: : Fast Sampling by Randomness Control in Irreversible Markov Chains
M. Michel, A. Durmus and S. Sénécal,
JCGS, 29 (4), 689-702 (2020).
Clock Monte Carlo methods
M. Michel, X. Tan and Y. Deng,
PRE, 99, 010105, Rapid Communication (2019).
Event-chain Monte Carlo algorithms for three- and many-particle interactions
J. Harland, M. Michel, T. A. Kampmann and J. Kierfeld,
EPL, 117, 30001 (2017) - editor's choice.
Event-chain algorithm for the Heisenberg model: Evidence for z ~ 1 dynamic scaling
Nishikawa Y., Michel M., Krauth W., Hukushima K.,
Physical Review E, 92, 063306 (2015).
Event-chain Monte Carlo for classical continuous spin models
Michel M., Mayer J., Krauth W.,
EPL, 112, 20003 (2015).
Generalized event-chain Monte Carlo: Constructing rejection-free global-balance algorithms from infinitesimal steps
Michel M., Kapfer S., Krauth W.,
Journal of Chemical Physics, 140, 054116 (2014).
Mass distributions of stars and cores in young groups and clusters
Michel M., Kirk H., Myers P.,
Astrophysical Journal, 735, 51 (2011).
Phd Thesis
Irreversible Markov chains by the factorized Metropolis filter: Algorithms and applications in particle systems and spin models
M. Michel, defended on October 17th, 2016 at ENS, Paris, France.