Tighter Variational Bounds are Not Necessarily Better

13 February 2018

Papers citing "Tighter Variational Bounds are Not Necessarily Better"

48 / 48 papers shown

Title
Bayesian Computation in Deep Learning Wenlong Chen Bolian Li Ruqi Zhang Yingzhen Li BDL 75 0 0 25 Feb 2025
Generative Adversarial Networks for High-Dimensional Item Factor Analysis: A Deep Adversarial Learning Algorithm Nanyu Luo Feng Ji DRL 41 0 0 15 Feb 2025
SoftCVI: Contrastive variational inference with self-generated soft labels Daniel Ward Mark Beaumont Matteo Fasiolo BDL 53 0 0 22 Jul 2024
Improving Variational Autoencoder Estimation from Incomplete Data with Mixture Variational Families Vaidotas Šimkus Michael U. Gutmann 43 2 0 05 Mar 2024
Delta-AI: Local objectives for amortized inference in sparse graphical models Jean-Pierre Falet Hae Beom Lee Nikolay Malkin Chen Sun Dragos Secrieru Thomas Jiralerspong Dinghuai Zhang Guillaume Lajoie Yoshua Bengio 51 6 0 03 Oct 2023
Autocodificadores Variacionales (VAE) Fundamentos Teóricos y Aplicaciones J. D. L. Torre DRL 20 1 0 18 Feb 2023
SeeGera: Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking Xiang Li Tiandi Ye Caihua Shan Dongsheng Li Ming Gao SSL 36 30 0 29 Jan 2023
Fast and Efficient Scene Categorization for Autonomous Driving using VAEs Saravanabalagi Ramachandran Jonathan Horgan Ganesh Sistu J. McDonald 3DV 29 1 0 26 Oct 2022
Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics Kamélia Daudel Joe Benton Yuyang Shi Arnaud Doucet DRL 19 8 0 12 Oct 2022
GFlowNets and variational inference Nikolay Malkin Salem Lahlou T. Deleu Xu Ji J. E. Hu Katie Everett Dinghuai Zhang Yoshua Bengio BDL 134 77 0 02 Oct 2022
Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs Ðorðe Miladinovic Kumar Shridhar Kushal Kumar Jain Max B. Paulus J. M. Buhmann Mrinmaya Sachan Carl Allen DRL 23 5 0 26 Sep 2022
Tighter Variational Bounds are Not Necessarily Better. A Research Report on Implementation, Ablation Study, and Extensions Amine MĆharrak Vít Ruzicka Sangyun Shin M. Vankadari DRL 6 0 0 23 Sep 2022
Variational Open-Domain Question Answering Valentin Liévin Andreas Geert Motzfeldt Ida Riis Jensen Ole Winther OOD BDL 36 8 0 23 Sep 2022
Bounding Evidence and Estimating Log-Likelihood in VAE Lukasz Struski Marcin Mazur Pawel Batorski Przemysław Spurek Jacek Tabor 21 3 0 19 Jun 2022
Mitigating Modality Collapse in Multimodal VAEs via Impartial Optimization Adrián Javaloy Maryam Meghdadi Isabel Valera 27 27 0 09 Jun 2022
Variational Sparse Coding with Learned Thresholding Kion Fallah Christopher Rozell DRL 23 7 0 07 May 2022
A Variational Approach to Bayesian Phylogenetic Inference Cheng Zhang IV FrederickA.Matsen BDL 24 17 0 16 Apr 2022
Variational methods for simulation-based inference Manuel Glöckler Michael Deistler Jakob H. Macke 30 46 0 08 Mar 2022
Variational Refinement for Importance Sampling Using the Forward Kullback-Leibler Divergence Ghassen Jerfel S. Wang Clara Fannjiang Katherine A. Heller Yi Ma Michael I. Jordan BDL 21 40 0 30 Jun 2021
Decomposed Mutual Information Estimation for Contrastive Representation Learning Alessandro Sordoni Nouha Dziri Hannes Schulz Geoffrey J. Gordon Philip Bachman Rémi Tachet des Combes SSL 24 29 0 25 Jun 2021
Variational Bayes in State Space Models: Inferential and Predictive Accuracy David T. Frazier Rubén Loaiza-Maya G. Martin 11 13 0 23 Jun 2021
Nested Variational Inference Heiko Zimmermann Hao Wu Babak Esmaeili Jan-Willem van de Meent BDL 27 20 0 21 Jun 2021
Differentiable Particle Filtering without Modifying the Forward Pass Adam Scibior Frank Wood 28 19 0 18 Jun 2021
Estimating the Unique Information of Continuous Variables Ari Pakman Amin Nejatbakhsh D. Gilboa Abdullah Makkeh Luca Mazzucato Michael Wibral E. Schneidman 43 24 0 30 Jan 2021
PAC $^m$ -Bayes: Narrowing the Empirical Risk Gap in the Misspecified Bayesian Regime Warren Morningstar Alexander A. Alemi Joshua V. Dillon 82 16 0 19 Oct 2020
Failure Modes of Variational Autoencoders and Their Effects on Downstream Tasks Yaniv Yacoby Weiwei Pan Finale Doshi-Velez CML DRL 27 25 0 14 Jul 2020
Variational Inference with Continuously-Indexed Normalizing Flows Anthony L. Caterini R. Cornish Dino Sejdinovic Arnaud Doucet BDL 24 19 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 6 16 0 01 Jul 2020
Advances in Black-Box VI: Normalizing Flows, Importance Weighting, and Optimization Abhinav Agrawal Daniel Sheldon Justin Domke TPM BDL 8 38 0 18 Jun 2020
Multimodal Generative Learning Utilizing Jensen-Shannon-Divergence Thomas M. Sutter Imant Daunhawer Julia E. Vogt 36 67 0 15 Jun 2020
Joint Stochastic Approximation and Its Application to Learning Discrete Latent Variable Models Zhijian Ou Yunfu Song BDL 32 8 0 28 May 2020
Amortised Learning by Wake-Sleep W. Li Theodore H. Moskovitz Heishiro Kanagawa M. Sahani OOD 23 7 0 22 Feb 2020
Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models Yuge Shi Siddharth Narayanaswamy Brooks Paige Philip Torr DRL 27 266 0 08 Nov 2019
Particle Smoothing Variational Objectives A. Moretti Zizhao Wang Luhuan Wu Iddo Drori I. Pe’er 21 10 0 20 Sep 2019
Mixed-Variable Bayesian Optimization Erik A. Daxberger Anastasia Makarova M. Turchetta Andreas Krause 24 51 0 02 Jul 2019
Explainable Anatomical Shape Analysis through Deep Hierarchical Generative Models C. Biffi Juan J. Cerrolaza G. Tarroni Wenjia Bai A. de Marvao ... Jinming Duan S. Prasad S. Cook D. O’Regan Daniel Rueckert MedIm 23 46 0 28 Jun 2019
Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation Justin Domke Daniel Sheldon 16 18 0 24 Jun 2019
Streaming Variational Monte Carlo Yuan Zhao Josue Nassar I. Jordan M. Bugallo Il Memming Park BDL 34 21 0 04 Jun 2019
Introducing Super Pseudo Panels: Application to Transport Preference Dynamics S. Borysov Jeppe Rich AI4TS 24 7 0 01 Mar 2019
Deconstructing Generative Adversarial Networks Banghua Zhu Jiantao Jiao David Tse 34 49 0 27 Jan 2019
MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Pierre-Alexandre Mattei J. Frellsen SyDa 25 45 0 06 Dec 2018
The Variational Deficiency Bottleneck P. Banerjee Guido Montúfar 15 7 0 27 Oct 2018
A Review of Learning with Deep Generative Models from Perspective of Graphical Modeling Zhijian Ou 31 16 0 05 Aug 2018
Semi-Implicit Variational Inference Mingzhang Yin Mingyuan Zhou BDL 35 121 0 28 May 2018
Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers Marcel Hirt P. Dellaportas BDL 20 10 0 23 May 2018
Semi-Amortized Variational Autoencoders Yoon Kim Sam Wiseman Andrew C. Miller David Sontag Alexander M. Rush BDL DRL 33 243 0 07 Feb 2018
Faithful Inversion of Generative Models for Effective Amortized Inference Stefan Webb Adam Goliñski R. Zinkov Siddharth Narayanaswamy Tom Rainforth Yee Whye Teh Frank Wood TPM 42 46 0 01 Dec 2017
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 38 684 0 15 Nov 2017