MetFlow: A New Efficient Method for Bridging the Gap between Markov
Chain Monte Carlo and Variational Inference

MetFlow: A New Efficient Method for Bridging the Gap between Markov Chain Monte Carlo and Variational Inference

27 February 2020

Nikita Kotelevskii

Jean-Stanislas Denain

Léo Grinsztajn

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Papers citing "MetFlow: A New Efficient Method for Bridging the Gap between Markov Chain Monte Carlo and Variational Inference"

13 / 13 papers shown

Title
Variational Learning of Gaussian Process Latent Variable Models through Stochastic Gradient Annealed Importance Sampling Jian Xu Shian Du Junmei Yang Qianli Ma Delu Zeng BDL 125 0 0 13 Aug 2024
Predictive Uncertainty Quantification via Risk Decompositions for Strictly Proper Scoring Rules Nikita Kotelevskii Maxim Panov PER UQCV UD 198 14 0 16 Feb 2024
Learning variational autoencoders via MCMC speed measuresStatistics and computing (Stat. Comput.), 2023 Marcel Hirt Vasileios Kreouzis P. Dellaportas BDL DRL 102 2 0 26 Aug 2023
Optimization of Annealed Importance Sampling Hyperparameters Shirin Goshtasbpour Fernando Perez-Cruz 187 1 0 27 Sep 2022
The Free Energy Principle for Perception and Action: A Deep Learning Perspective Pietro Mazzaglia Tim Verbelen Ozan Çatal Bart Dhoedt DRL AI4CE 128 36 0 13 Jul 2022
Multimodal Maximum Entropy Dynamic Games Oswin So Kyle Stachowicz Evangelos A. Theodorou 192 9 0 30 Jan 2022
Annealed Flow Transport Monte CarloInternational Conference on Machine Learning (ICML), 2021 Michael Arbel A. G. Matthews Arnaud Doucet 184 90 0 15 Feb 2021
Nonreversible MCMC from conditional invertible transforms: a complete recipe with convergence guarantees Achille Thin Nikita Kotolevskii Christophe Andrieu Alain Durmus Eric Moulines Maxim Panov 158 6 0 31 Dec 2020
A general perspective on the Metropolis-Hastings kernel Christophe Andrieu Anthony Lee Samuel Livingstone 153 27 0 29 Dec 2020
Accelerating MCMC algorithms through Bayesian Deep Networks Héctor J. Hortúa Riccardo Volpi D. Marinelli Luigi Malagò BDL 69 13 0 29 Nov 2020
Measure Transport with Kernel Stein Discrepancy Matthew A. Fisher T. Nolan Matthew M. Graham D. Prangle Chris J. Oates OT 189 15 0 22 Oct 2020
Qualitative Analysis of Monte Carlo Dropout Ronald Seoh UQCV BDL 82 30 0 03 Jul 2020
Constraining the Reionization History using Bayesian Normalizing Flows Héctor J. Hortúa Luigi Malagò Riccardo Volpi BDL 74 20 0 14 May 2020