Inference Suboptimality in Variational Autoencoders

10 January 2018

Papers citing "Inference Suboptimality in Variational Autoencoders"

50 / 62 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
When the whole is greater than the sum of its parts: Scaling black-box inference to large data settings through divide-and-conquer Emily C. Hector Amanda Lenzi 41 1 0 31 Dec 2024
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation M. Valiuddin R. V. Sloun C.G.A. Viviers Peter H. N. de With Fons van der Sommen UQCV 91 1 0 25 Nov 2024
Brain-like variational inference Hadi Vafaii Dekel Galor Jacob L. Yates DRL 49 0 0 25 Oct 2024
Improving Variational Autoencoder Estimation from Incomplete Data with Mixture Variational Families Vaidotas Šimkus Michael U. Gutmann 37 2 0 05 Mar 2024
Domain Generalization with Small Data Kecheng Chen Elena Gal Hong Yan Haoliang Li OOD 27 5 0 09 Feb 2024
Robustly overfitting latents for flexible neural image compression Yura Perugachi-Diaz Arwin Gansekoele S. Bhulai 36 1 0 31 Jan 2024
Variational Distribution Learning for Unsupervised Text-to-Image Generation Minsoo Kang Doyup Lee Jiseob Kim Saehoon Kim Bohyung Han DRL OOD 16 3 0 28 Mar 2023
Unsupervised Domain Adaptation for Low-dose CT Reconstruction via Bayesian Uncertainty Alignment Kecheng Chen Jie Liu Renjie Wan Victor Ho-Fun Lee Varut Vardhanabhuti Hong Yan Haoliang Li OOD 26 5 0 26 Feb 2023
Variational Mixture of HyperGenerators for Learning Distributions Over Functions Batuhan Koyuncu Pablo Sánchez-Martín I. Peis Pablo Martínez Olmos Isabel Valera BDL GAN DRL 22 5 0 13 Feb 2023
DGNet: Distribution Guided Efficient Learning for Oil Spill Image Segmentation Fang Chen H. Balzter Feixiang Zhou Pengxin Ren Huiyu Zhou 25 13 0 19 Dec 2022
Variational Laplace Autoencoders Yookoon Park C. Kim Gunhee Kim BDL DRL 26 21 0 30 Nov 2022
Toward Adaptive Semantic Communications: Efficient Data Transmission via Online Learned Nonlinear Transform Source-Channel Coding Jincheng Dai Sixian Wang Ke Yang Kailin Tan Xiaoqi Qin Zhongwei Si K. Niu Ping Zhang 23 19 0 08 Nov 2022
Reducing The Mismatch Between Marginal and Learned Distributions in Neural Video Compression M. Balcilar B. Damodaran Pierre Hellier 23 2 0 12 Oct 2022
Improving The Reconstruction Quality by Overfitted Decoder Bias in Neural Image Compression Oussama Jourairi M. Balcilar Anne Lambert Franccois Schnitzler 15 4 0 10 Oct 2022
Variational Open-Domain Question Answering Valentin Liévin Andreas Geert Motzfeldt Ida Riis Jensen Ole Winther OOD BDL 31 8 0 23 Sep 2022
Bit Allocation using Optimization Tongda Xu Han-yi Gao Chenjian Gao Yuanyuan Wang Dailan He ... Mao Ye Hongwei Qin Yan Wang Jingjing Liu Ya-Qin Zhang 56 14 0 20 Sep 2022
Flexible Neural Image Compression via Code Editing Chenjian Gao Tongda Xu Dailan He Hongwei Qin Yan Wang 46 24 0 19 Sep 2022
A Geometric Perspective on Variational Autoencoders Clément Chadebec S. Allassonnière DRL 29 21 0 15 Sep 2022
Reducing The Amortization Gap of Entropy Bottleneck In End-to-End Image Compression M. Balcilar B. Damodaran Pierre Hellier 19 8 0 02 Sep 2022
Generalization Gap in Amortized Inference Mingtian Zhang Peter Hayes David Barber BDL CML DRL 45 14 0 23 May 2022
Hybrid Predictive Coding: Inferring, Fast and Slow Alexander Tschantz Beren Millidge A. Seth Christopher L. Buckley 24 36 0 05 Apr 2022
Alleviating Adversarial Attacks on Variational Autoencoders with MCMC Anna Kuzina Max Welling Jakub M. Tomczak AAML DRL 31 12 0 18 Mar 2022
Model-agnostic out-of-distribution detection using combined statistical tests Federico Bergamin Pierre-Alexandre Mattei Jakob Drachmann Havtorn Hugo Senetaire Hugo Schmutz Lars Maaløe Søren Hauberg J. Frellsen OODD 21 18 0 02 Mar 2022
Tutorial on amortized optimization Brandon Amos OffRL 75 43 0 01 Feb 2022
Unsupervised Representation Learning via Neural Activation Coding Yookoon Park Sangho Lee Gunhee Kim David M. Blei SSL 21 8 0 07 Dec 2021
Counterfactual Explanations via Latent Space Projection and Interpolation Brian Barr Matthew R. Harrington Samuel Sharpe Capital One BDL 28 10 0 02 Dec 2021
Exploring Versatile Prior for Human Motion via Motion Frequency Guidance Jiachen Xu Min Wang Jing-yu Gong Wentao Liu Chao Qian Yuan Xie Lizhuang Ma 27 9 0 25 Nov 2021
Relay Variational Inference: A Method for Accelerated Encoderless VI Amir Zadeh Santiago Benoit Louis-Philippe Morency DRL 17 1 0 26 Oct 2021
Learning Opinion Summarizers by Selecting Informative Reviews Arthur Brazinskas Mirella Lapata Ivan Titov 45 29 0 09 Sep 2021
Meta-learning Amidst Heterogeneity and Ambiguity Kyeongryeol Go Seyoung Yun 24 1 0 05 Jul 2021
ADAVI: Automatic Dual Amortized Variational Inference Applied To Pyramidal Bayesian Models Louis Rouillard Demian Wassermann 33 2 0 23 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 36 61 0 30 Apr 2021
NeRF-VAE: A Geometry Aware 3D Scene Generative Model Adam R. Kosiorek Heiko Strathmann Daniel Zoran Pol Moreno R. Schneider Sovna Mokrá Danilo Jimenez Rezende DRL 29 139 0 01 Apr 2021
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models Sam Bond-Taylor Adam Leach Yang Long Chris G. Willcocks VLM TPM 36 480 0 08 Mar 2021
Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design Adam Foster Desi R. Ivanova Ilyas Malik Tom Rainforth 28 78 0 03 Mar 2021
COIN: COmpression with Implicit Neural representations Emilien Dupont Adam Goliñski Milad Alizadeh Yee Whye Teh Arnaud Doucet 20 223 0 03 Mar 2021
Direct Evolutionary Optimization of Variational Autoencoders With Binary Latents E. Guiraud Jakob Drefs Jörg Lücke DRL 33 3 0 27 Nov 2020
Geometry-Aware Hamiltonian Variational Auto-Encoder Clément Chadebec Clément Mantoux S. Allassonnière DRL 17 15 0 22 Oct 2020
Neural Network-based Reconstruction in Compressed Sensing MRI Without Fully-sampled Training Data Alan Q. Wang Adrian V. Dalca M. Sabuncu 31 26 0 29 Jul 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
Control as Hybrid Inference Alexander Tschantz Beren Millidge A. Seth Christopher L. Buckley 19 9 0 11 Jul 2020
Bayesian Neural Networks: An Introduction and Survey Ethan Goan Clinton Fookes BDL UQCV 32 199 0 22 Jun 2020
A Batch Normalized Inference Network Keeps the KL Vanishing Away Qile Zhu Jianlin Su Wei Bi Xiaojiang Liu Xiyao Ma Xiaolin Li D. Wu BDL DRL 34 61 0 27 Apr 2020
Going in circles is the way forward: the role of recurrence in visual inference R. S. V. Bergen N. Kriegeskorte 17 81 0 26 Mar 2020
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models Chin-Wei Huang Laurent Dinh Aaron Courville DRL 31 87 0 17 Feb 2020
Don't Blame the ELBO! A Linear VAE Perspective on Posterior Collapse James Lucas George Tucker Roger C. Grosse Mohammad Norouzi CoGe DRL 16 179 0 06 Nov 2019
Balancing Reconstruction Quality and Regularisation in ELBO for VAEs Shuyu Lin Stephen J. Roberts Niki Trigoni R. Clark DRL 18 15 0 09 Sep 2019
Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations Jan Stühmer Richard E. Turner Sebastian Nowozin DRL BDL CoGe 111 25 0 05 Sep 2019