f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization

2 June 2016

Papers citing "f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization"

35 / 35 papers shown

Title
Inverse-RLignment: Large Language Model Alignment from Demonstrations through Inverse Reinforcement Learning Hao Sun M. Schaar 105 16 0 28 Jan 2025
Nested Annealed Training Scheme for Generative Adversarial Networks Chang Wan Ming-Hsuan Yang Minglu Li Yunliang Jiang Zhonglong Zheng GAN 77 0 0 20 Jan 2025
Enhancing Graph Self-Supervised Learning with Graph Interplay Xinjian Zhao Wei Pang Xiangru Jian Yaoyao Xu Chaolong Ying Tianshu Yu 116 0 0 17 Jan 2025
$f$ -PO: Generalizing Preference Optimization with $f$ -divergence Minimization Jiaqi Han Mingjian Jiang Yuxuan Song J. Leskovec Stefano Ermon 71 5 0 29 Oct 2024
Bounds on Lp errors in density ratio estimation via f-divergence loss functions Yoshiaki Kitazawa 57 0 0 02 Oct 2024
HiLo: A Learning Framework for Generalized Category Discovery Robust to Domain Shifts Hongjun Wang S. Vaze Kai Han 107 4 0 08 Aug 2024
MCGAN: Enhancing GAN Training with Regression-Based Generator Loss Baoren Xiao Hao Ni Weixin Yang GAN 88 0 0 27 May 2024
Contrastive Multi-View Representation Learning on Graphs Kaveh Hassani Amir Hosein Khas Ahmadi SSL 180 1,284 0 10 Jun 2020
Conditional Mutual Information Neural Estimator Sina Molavipour Germán Bassi Mikael Skoglund 43 14 0 06 Nov 2019
From optimal transport to generative modeling: the VEGAN cookbook Olivier Bousquet Sylvain Gelly Ilya O. Tolstikhin Carl-Johann Simon-Gabriel B. Schoelkopf OT 39 147 0 22 May 2017
Wasserstein GAN Martín Arjovsky Soumith Chintala Léon Bottou GAN 131 4,817 0 26 Jan 2017
Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks L. Mescheder Sebastian Nowozin Andreas Geiger GAN BDL 82 528 0 17 Jan 2017
NIPS 2016 Tutorial: Generative Adversarial Networks Ian Goodfellow GAN 83 1,721 0 31 Dec 2016
Amortised MAP Inference for Image Super-resolution C. Sønderby Jose Caballero Lucas Theis Wenzhe Shi Ferenc Huszár 68 435 0 14 Oct 2016
Generative Adversarial Nets from a Density Ratio Estimation Perspective Masatoshi Uehara Issei Sato Masahiro Suzuki Kotaro Nakayama Y. Matsuo GAN 58 104 0 10 Oct 2016
Improved Techniques for Training GANs Tim Salimans Ian Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford Xi Chen GAN 353 8,999 0 10 Jun 2016
Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) Djork-Arné Clevert Thomas Unterthiner Sepp Hochreiter 194 5,502 0 23 Nov 2015
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks Alec Radford Luke Metz Soumith Chintala GAN OOD 226 13,968 0 19 Nov 2015
Adversarial Autoencoders Alireza Makhzani Jonathon Shlens Navdeep Jaitly Ian Goodfellow Brendan J. Frey GAN 63 2,224 0 18 Nov 2015
How (not) to Train your Generative Model: Scheduled Sampling, Likelihood, Adversary? Ferenc Huszár OOD DiffM GAN 43 296 0 16 Nov 2015
A note on the evaluation of generative models Lucas Theis Aaron van den Oord Matthias Bethge EGVM 61 1,139 0 05 Nov 2015
LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop Feng Yu Ari Seff Yinda Zhang Shuran Song Thomas Funkhouser Jianxiong Xiao 37 2,320 0 10 Jun 2015
Training generative neural networks via Maximum Mean Discrepancy optimization Gintare Karolina Dziugaite Daniel M. Roy Zoubin Ghahramani GAN 66 528 0 14 May 2015
Deep Unsupervised Learning using Nonequilibrium Thermodynamics Jascha Narain Sohl-Dickstein Eric A. Weiss Niru Maheswaranathan Surya Ganguli SyDa DiffM 173 6,780 0 12 Mar 2015
Generative Moment Matching Networks Yujia Li Kevin Swersky R. Zemel OOD GAN 86 844 0 10 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 673 149,474 0 22 Dec 2014
On distinguishability criteria for estimating generative models Ian Goodfellow GAN 35 138 0 19 Dec 2014
Identifying and attacking the saddle point problem in high-dimensional non-convex optimization Yann N. Dauphin Razvan Pascanu Çağlar Gülçehre Kyunghyun Cho Surya Ganguli Yoshua Bengio ODL 95 1,379 0 10 Jun 2014
Neural Variational Inference and Learning in Belief Networks A. Mnih Karol Gregor BDL 95 727 0 31 Jan 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 344 16,972 0 20 Dec 2013
Generating Sequences With Recurrent Neural Networks Alex Graves GAN 97 4,025 0 04 Aug 2013
RNADE: The real-valued neural autoregressive density-estimator Benigno Uria Iain Murray Hugo Larochelle 74 237 0 02 Jun 2013
Hilbert space embeddings and metrics on probability measures Bharath K. Sriperumbudur Arthur Gretton Kenji Fukumizu Bernhard Schölkopf Gert R. G. Lanckriet 147 741 0 30 Jul 2009
Information, Divergence and Risk for Binary Experiments Mark D. Reid Robert C. Williamson 79 231 0 05 Jan 2009
Estimating divergence functionals and the likelihood ratio by convex risk minimization X. Nguyen Martin J. Wainwright Michael I. Jordan 141 799 0 04 Sep 2008