Intermediate filaments in peripheral nervous system: Their expression, dysfunction and diseases

Autor: Parlakian, A., Paulin, D., Izmiryan, A., Xue, Z., Li, Z.

Publikováno v: In Revue Neurologique October 2016 172(10):607-613

Tropomyosin Synthesis Accompanies Formation of Actin Filaments in Embryonal Carcinoma Cells Induced to Differentiate by Hexamethylene Bisacetamide

Autor: Paulin, D., Perreau, J., Jakob, H., Jacob, F., Yaniv, M.

Publikováno v: Proceedings of the National Academy of Sciences of the United States of America, 1979 Apr 01. 76(4), 1891-1895.

Externí odkaz: https://www.jstor.org/stable/69620

Randomized Hamiltonian Monte Carlo as scaling limit of the bouncy particle sampler and dimension-free convergence rates

Autor: Deligiannidis, G, Paulin, D, Bouchard-Côté, A, Doucet, A

Publikováno v: Deligiannidis, G, Paulin, D, Bouchard-Côté, A & Doucet, A 2021, ' Randomized Hamiltonian Monte Carlo as Scaling Limit of the Bouncy Particle Sampler and Dimension-Free Convergence Rates ', Annals of Applied Probability, vol. 31, no. 6, pp. 2612-2662 . https://doi.org/10.1214/20-AAP1659

The Bouncy Particle Sampler is a Markov chain Monte Carlo method based on a nonreversible piecewise deterministic Markov process. In this scheme, a particle explores the state space of interest by evolving according to a linear dynamics which is alte

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94feb0b4528afae3e82a5aaf1137ad6f
https://ora.ox.ac.uk/objects/uuid:954bfaa2-ae69-41dd-99fd-5fc3bf535fd0

Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting

Autor: Vono, M, Paulin, D, Doucet, A

Performing exact Bayesian inference for complex models is computationally intractable. Markov chain Monte Carlo (MCMC) algorithms can provide reliable approximations of the posterior distribution but are expensive for large datasets and high-dimensio

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::da20f96dd2a764bab63acca88d22c8b2
http://arxiv.org/abs/1905.11937

Hybrid ground-state quantum algorithms based on neural Schrödinger forging

Autor: Paulin de Schoulepnikoff, Oriel Kiss, Sofia Vallecorsa, Giuseppe Carleo, Michele Grossi

Publikováno v: Physical Review Research, Vol 6, Iss 2, p 023021 (2024)

Entanglement forging based variational algorithms leverage the bipartition of quantum systems for addressing ground-state problems. The primary limitation of these approaches lies in the exponential summation required over the numerous potential basi

Externí odkaz: https://doaj.org/article/5dc7494a6be742da9cd911037457aa18