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Hamiltonian Variational Auto-Encoder

29 May 2018

Dino Sejdinovic

Papers citing "Hamiltonian Variational Auto-Encoder"

40 / 40 papers shown

Title
Bidirectional Variational Autoencoders Bart Kosko Olaoluwa Adigun BDL 83 0 0 21 May 2025
Bayesian Computation in Deep Learning Wenlong Chen Bolian Li Ruqi Zhang Yingzhen Li BDL 114 0 0 25 Feb 2025
Low-Dimensional Representation-Driven TSK Fuzzy System for Feature Selection Qiong Liu Mingjie Cai Qingguo Li 81 0 0 22 Jan 2025
Improved Variational Inference in Discrete VAEs using Error Correcting Codes María Martínez-García Grace Villacrés David Mitchell Pablo Martínez Olmos DRL 94 0 0 10 Oct 2024
Deep Learning Approaches for Data Augmentation in Medical Imaging: A Review Aghiles Kebaili J. Lapuyade-Lahorgue S. Ruan MedIm 88 156 0 24 Jul 2023
One-Line-of-Code Data Mollification Improves Optimization of Likelihood-based Generative Models Ba-Hien Tran Giulio Franzese Pietro Michiardi Maurizio Filippone DiffM 128 4 0 30 May 2023
Variational Inference for Longitudinal Data Using Normalizing Flows Clément Chadebec S. Allassonnière BDL DRL 49 1 0 24 Mar 2023
Approaching Globally Optimal Energy Efficiency in Interference Networks via Machine Learning Bile Peng Karl-Ludwig Besser Ramprasad Raghunath Eduard Axel Jorswieck 38 2 0 25 Nov 2022
Optimization of Annealed Importance Sampling Hyperparameters Shirin Goshtasbpour Fernando Perez-Cruz 58 1 0 27 Sep 2022
A Geometric Perspective on Variational Autoencoders Clément Chadebec S. Allassonnière DRL 93 24 0 15 Sep 2022
Langevin Diffusion Variational Inference Tomas Geffner Justin Domke DiffM 75 24 0 16 Aug 2022
Pythae: Unifying Generative Autoencoders in Python -- A Benchmarking Use Case Clément Chadebec Louis J. Vincent S. Allassonnière DRL 98 30 0 16 Jun 2022
Bayesian inference via sparse Hamiltonian flows Na Chen Zuheng Xu Trevor Campbell 85 14 0 11 Mar 2022
Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte Carlo I. Peis Chao Ma José Miguel Hernández-Lobato BDL DRL 88 15 0 09 Feb 2022
Surrogate Likelihoods for Variational Annealed Importance Sampling M. Jankowiak Du Phan BDL 79 13 0 22 Dec 2021
Auto-Encoding Score Distribution Regression for Action Quality Assessment Boyu Zhang Jiayuan Chen Yinfei Xu Hui Zhang Xu Yang Xin Geng 89 28 0 22 Nov 2021
Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling Greg Ver Steeg Aram Galstyan 80 15 0 03 Nov 2021
Variational Marginal Particle Filters Jinlin Lai Justin Domke Daniel Sheldon 92 9 0 30 Sep 2021
Differentiable Annealed Importance Sampling and the Perils of Gradient Noise Guodong Zhang Kyle Hsu Jianing Li Chelsea Finn Roger C. Grosse 85 40 0 21 Jul 2021
MCMC Variational Inference via Uncorrected Hamiltonian Annealing Tomas Geffner Justin Domke 86 36 0 08 Jul 2021
Monte Carlo Variational Auto-Encoders Achille Thin Nikita Kotelevskii Arnaud Doucet Alain Durmus Eric Moulines Maxim Panov BDL DRL 67 45 0 30 Jun 2021
Nested Variational Inference Heiko Zimmermann Hao Wu Babak Esmaeili Jan-Willem van de Meent BDL 80 21 0 21 Jun 2021
Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder Clément Chadebec Elina Thibeau-Sutre Ninon Burgos S. Allassonnière 126 69 0 30 Apr 2021
Improving Actor-Critic Reinforcement Learning via Hamiltonian Monte Carlo Method Duo Xu Faramarz Fekri 58 8 0 22 Mar 2021
Learning Proposals for Probabilistic Programs with Inference Combinators Sam Stites Heiko Zimmermann Hao Wu Eli Sennesh Jan-Willem van de Meent NAI 84 16 0 01 Mar 2021
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding Yangjun Ruan Karen Ullrich Daniel de Souza Severo James Townsend Ashish Khisti Arnaud Doucet Alireza Makhzani Chris J. Maddison 101 25 0 22 Feb 2021
Annealed Flow Transport Monte Carlo Michael Arbel A. G. Matthews Arnaud Doucet 93 78 0 15 Feb 2021
Factor Analysis, Probabilistic Principal Component Analysis, Variational Inference, and Variational Autoencoder: Tutorial and Survey Benyamin Ghojogh A. Ghodsi Fakhri Karray Mark Crowley DRL 52 37 0 04 Jan 2021
Measure Transport with Kernel Stein Discrepancy Matthew A. Fisher T. Nolan Matthew M. Graham D. Prangle Chris J. Oates OT 124 15 0 22 Oct 2020
Geometry-Aware Hamiltonian Variational Auto-Encoder Clément Chadebec Clément Mantoux S. Allassonnière DRL 84 16 0 22 Oct 2020
Quasi-symplectic Langevin Variational Autoencoder Zihao Wang H. Delingette BDL DRL 73 4 0 02 Sep 2020
Variational Inference with Continuously-Indexed Normalizing Flows Anthony L. Caterini R. Cornish Dino Sejdinovic Arnaud Doucet BDL 73 20 0 10 Jul 2020
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference Rob Brekelmans Vaden Masrani Frank Wood Greg Ver Steeg Aram Galstyan 57 16 0 01 Jul 2020
MetFlow: A New Efficient Method for Bridging the Gap between Markov Chain Monte Carlo and Variational Inference Achille Thin Nikita Kotelevskii Jean-Stanislas Denain Léo Grinsztajn Alain Durmus Maxim Panov Eric Moulines BDL 55 17 0 27 Feb 2020
Amortized Population Gibbs Samplers with Neural Sufficient Statistics Hao Wu Heiko Zimmermann Eli Sennesh T. Le Jan-Willem van de Meent 53 7 0 04 Nov 2019
Variational Integrator Networks for Physically Structured Embeddings Steindór Sæmundsson Alexander Terenin Katja Hofmann M. Deisenroth GNN AI4CE 81 50 0 21 Oct 2019
Learning Symmetries of Classical Integrable Systems Roberto Bondesan A. Lamacraft 80 40 0 11 Jun 2019
Exponential Family Estimation via Adversarial Dynamics Embedding Bo Dai Ziqiang Liu H. Dai Niao He Arthur Gretton Le Song Dale Schuurmans 82 53 0 27 Apr 2019
NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport Matthew Hoffman Pavel Sountsov Joshua V. Dillon I. Langmore Dustin Tran Srinivas Vasudevan BDL 73 108 0 09 Mar 2019
Ergodic Inference: Accelerate Convergence by Optimisation Yichuan Zhang José Miguel Hernández-Lobato BDL 77 9 0 25 May 2018