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Achille Thin
Achille Thin
AgroParisTech
Verified email at polytechnique.edu
Title
Cited by
Cited by
Year
Monte Carlo variational auto-encoders
A Thin, N Kotelevskii, A Doucet, A Durmus, E Moulines, M Panov
International Conference on Machine Learning, 10247-10257, 2021
362021
NEO: Non Equilibrium Sampling on the Orbit of a Deterministic Transform
A Thin, Y Janati, S Le Corff, C Ollion, A Doucet, A Durmus, E Moulines, ...
21*2021
First modeling of strongly radiating WEST plasmas with SOLEDGE-EIRENE
G Ciraolo, A Thin, H Bufferand, J Bucalossi, N Fedorczak, JP Gunn, ...
Nuclear Materials and Energy 20, 100685, 2019
152019
MetFlow: a new efficient method for bridging the gap between Markov chain Monte Carlo and variational inference
A Thin, N Kotelevskii, JS Denain, L Grinsztajn, A Durmus, M Panov, ...
arXiv preprint arXiv:2002.12253, 2020
142020
Differentiable samplers for deep latent variable models
A Doucet, E Moulines, A Thin
Philosophical Transactions of the Royal Society A 381 (2247), 20220147, 2023
62023
Nonreversible MCMC from conditional invertible transforms: a complete recipe with convergence guarantees
A Thin, N Kotelevskii, C Andrieu, A Durmus, E Moulines, M Panov
arXiv preprint arXiv:2012.15550, 2020
62020
Br-snis: bias reduced self-normalized importance sampling
G Cardoso, S Samsonov, A Thin, E Moulines, J Olsson
Advances in Neural Information Processing Systems 35, 716-729, 2022
32022
Metropolized flow: from invertible flow to mcmc
A Thin, N Kotelevskii, A Durmus, M Panov, E Moulines
Proceedings of the ICML Workshop on Invertible Neural Networks, Normalizing …, 2020
32020
Ex2MCMC: Sampling through Exploration Exploitation
E Lagutin, D Selikhanovych, A Thin, S Samsonov, A Naumov, ...
stat, 2022
22022
A validated correction method to quantify organic and inorganic carbon in soils using Rock-Eval® thermal analysis
M Stojanova, P Arbelet, F Baudin, N Bouton, G Caria, L Pacini, N Proix, ...
EGUsphere 2024, 1-12, 2024
2024
Nouvelles Méthodes Variationnelles pour l'inférence et l'apprentissage
A Thin
Institut polytechnique de Paris, 2022
2022
Novel Variational Approaches to Inference and Learning
A Thin
Institut Polytechnique de Paris, 2022
2022
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