Stochastic Backpropagation and Approximate Inference in Deep Generative Models

16 January 2014

Danilo Jimenez Rezende

Papers citing "Stochastic Backpropagation and Approximate Inference in Deep Generative Models"

31 / 31 papers shown

Title
Soft Neighbors are Positive Supporters in Contrastive Visual Representation Learning Chongjian Ge Jiangliu Wang Zhan Tong Shoufa Chen Yibing Song Ping Luo SSL 22 27 0 30 Mar 2023
Generalization Gap in Amortized Inference Mingtian Zhang Peter Hayes David Barber BDL CML DRL 45 14 0 23 May 2022
Multiple Importance Sampling ELBO and Deep Ensembles of Variational Approximations Oskar Kviman Harald Melin Hazal Koptagel Victor Elvira J. Lagergren DRL 75 17 0 22 Feb 2022
Revitalizing CNN Attentions via Transformers in Self-Supervised Visual Representation Learning Chongjian Ge Youwei Liang Yibing Song Jianbo Jiao Jue Wang Ping Luo ViT 24 36 0 11 Oct 2021
Entropic Issues in Likelihood-Based OOD Detection Anthony L. Caterini G. Loaiza-Ganem OODD 24 15 0 22 Sep 2021
Desiderata for Representation Learning: A Causal Perspective Yixin Wang Michael I. Jordan CML 32 82 0 08 Sep 2021
Sawtooth Factorial Topic Embeddings Guided Gamma Belief Network Zhibin Duan Dongsheng Wang Bo Chen Chaojie Wang Wenchao Chen Yewen Li Jie Ren Mingyuan Zhou BDL 37 38 0 30 Jun 2021
Reducing the Computational Cost of Deep Generative Models with Binary Neural Networks Thomas Bird F. Kingma David Barber SyDa MQ AI4CE 26 9 0 26 Oct 2020
Generative Neurosymbolic Machines Jindong Jiang Sungjin Ahn BDL OCL 225 68 0 23 Oct 2020
Bootstrap your own latent: A new approach to self-supervised Learning Jean-Bastien Grill Florian Strub Florent Altché Corentin Tallec Pierre Harvey Richemond ... M. G. Azar Bilal Piot Koray Kavukcuoglu Rémi Munos Michal Valko SSL 131 6,665 0 13 Jun 2020
Variational Autoencoders with Riemannian Brownian Motion Priors Dimitris Kalatzis David Eklund Georgios Arvanitidis Søren Hauberg BDL DRL 60 48 0 12 Feb 2020
Hybrid Generative-Discriminative Models for Inverse Materials Design Phuoc Nguyen T. Tran Sunil R. Gupta Santu Rana Svetha Venkatesh AI4CE PINN 13 6 0 31 Oct 2018
Probabilistic Meta-Representations Of Neural Networks Theofanis Karaletsos Peter Dayan Zoubin Ghahramani BDL 12 27 0 01 Oct 2018
Show, Attend and Translate: Unsupervised Image Translation with Self-Regularization and Attention Chao Yang Taehwan Kim Ruizhe Wang Hao Peng C.-C. Jay Kuo 28 51 0 16 Jun 2018
Only Bayes should learn a manifold (on the estimation of differential geometric structure from data) Søren Hauberg 13 31 0 13 Jun 2018
Maximizing acquisition functions for Bayesian optimization James T. Wilson Frank Hutter M. Deisenroth 46 240 0 25 May 2018
The Blessings of Multiple Causes Yixin Wang David M. Blei AI4CE CML 24 284 0 17 May 2018
DIY Human Action Data Set Generation Mehran Khodabandeh Hamid Reza Vaezi Joze Ilya Zharkov V. Pradeep 21 11 0 29 Mar 2018
Auto-Differentiating Linear Algebra Matthias Seeger A. Hetzel Zhenwen Dai Eric Meissner Neil D. Lawrence 17 38 0 24 Oct 2017
MoCoGAN: Decomposing Motion and Content for Video Generation Sergey Tulyakov Ming Liu Xiaodong Yang Jan Kautz GAN 93 1,131 0 17 Jul 2017
Improved generator objectives for GANs Ben Poole Alexander A. Alemi Jascha Narain Sohl-Dickstein A. Angelova 25 70 0 08 Dec 2016
Unrolled Generative Adversarial Networks Luke Metz Ben Poole David Pfau Jascha Narain Sohl-Dickstein GAN 59 1,001 0 07 Nov 2016
SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient Lantao Yu Weinan Zhang Jun Wang Yong Yu GAN 20 2,385 0 18 Sep 2016
Chained Gaussian Processes Alan D. Saul J. Hensman Aki Vehtari Neil D. Lawrence 16 59 0 18 Apr 2016
Generating Images from Captions with Attention Elman Mansimov Emilio Parisotto Jimmy Lei Ba Ruslan Salakhutdinov VLM 43 449 0 09 Nov 2015
Hierarchical Variational Models Rajesh Ranganath Dustin Tran David M. Blei DRL VLM 23 335 0 07 Nov 2015
Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning S. Mohamed Danilo Jimenez Rezende DRL SSL 8 399 0 29 Sep 2015
Deep Unsupervised Learning using Nonequilibrium Thermodynamics Jascha Narain Sohl-Dickstein Eric A. Weiss Niru Maheswaranathan Surya Ganguli SyDa DiffM 79 6,608 0 12 Mar 2015
Learning Stochastic Recurrent Networks Justin Bayer Christian Osendorfer BDL 40 273 0 27 Nov 2014
Techniques for Learning Binary Stochastic Feedforward Neural Networks T. Raiko Mathias Berglund Guillaume Alain Laurent Dinh BDL 65 126 0 11 Jun 2014
Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets Diederik P. Kingma Max Welling BDL 38 61 0 03 Feb 2014