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"

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Title
Learning Graph Augmentations to Learn Graph Representations Kaveh Hassani Amir Hosein Khas Ahmadi 110 21 0 24 Jan 2022
Toward Enhanced Robustness in Unsupervised Graph Representation Learning: A Graph Information Bottleneck Perspective Jihong Wang Minnan Luo Jundong Li Ziqi Liu Jun Zhou Qinghua Zheng AAML 58 5 0 21 Jan 2022
Informative Pseudo-Labeling for Graph Neural Networks with Few Labels Yayong Li Jie Yin Ling-Hao Chen 70 36 0 20 Jan 2022
On Sampling Collaborative Filtering Datasets Noveen Sachdeva Carole-Jean Wu Julian McAuley 78 16 0 13 Jan 2022
Disentanglement and Generalization Under Correlation Shifts Christina M. Funke Paul Vicol Kuan-Chieh Wang Matthias Kümmerer R. Zemel Matthias Bethge OOD 114 7 0 29 Dec 2021
Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization Lorenzo Pacchiardi Rilwan A. Adewoyin P. Dueben Ritabrata Dutta AI4TS 116 26 0 15 Dec 2021
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs Zhisheng Xiao Karsten Kreis Arash Vahdat DiffM 131 562 0 15 Dec 2021
CLIP-Lite: Information Efficient Visual Representation Learning with Language Supervision A. Shrivastava Ramprasaath R. Selvaraju Nikhil Naik Vicente Ordonez VLM CLIP 64 6 0 14 Dec 2021
Multi-Modal Mutual Information Maximization: A Novel Approach for Unsupervised Deep Cross-Modal Hashing Tuan Hoang Thanh-Toan Do Tam V. Nguyen Ngai-Man Cheung 74 26 0 13 Dec 2021
Computing Divergences between Discrete Decomposable Models Loong Kuan Lee Nico Piatkowski Franccois Petitjean Geoffrey I. Webb 27 2 0 08 Dec 2021
A Unified Framework for Multi-distribution Density Ratio Estimation Lantao Yu Yujia Jin Stefano Ermon 44 4 0 07 Dec 2021
Variational Wasserstein gradient flow JiaoJiao Fan Qinsheng Zhang Amirhossein Taghvaei Yongxin Chen 167 57 0 04 Dec 2021
The Representation Jensen-Rényi Divergence J. Hoyos-Osorio Oscar Skean A. Brockmeier L. S. Giraldo 47 2 0 02 Dec 2021
Generative Adversarial Networks and Adversarial Autoencoders: Tutorial and Survey Benyamin Ghojogh A. Ghodsi Fakhri Karray Mark Crowley GAN 111 12 0 26 Nov 2021
Density Ratio Estimation via Infinitesimal Classification Kristy Choi Chenlin Meng Yang Song Stefano Ermon 83 42 0 22 Nov 2021
Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data Liming Jiang Bo Dai Wayne Wu Chen Change Loy 137 109 0 12 Nov 2021
A Reverse Jensen Inequality Result with Application to Mutual Information Estimation Gerhard Wunder Benedikt Groß Rick Fritschek Rafael F. Schaefer 48 10 0 12 Nov 2021
Training Generative Adversarial Networks with Adaptive Composite Gradient Huiqing Qi Fang Li Shengli Tan Xiangyun Zhang GAN 53 4 0 10 Nov 2021
Speaker Generation Daisy Stanton Matt Shannon Soroosh Mariooryad RJ Skerry-Ryan Eric Battenberg Tom Bagby David Kao 96 30 0 07 Nov 2021
Variational Inference with Holder Bounds Junya Chen Danni Lu Zidi Xiu Ke Bai Lawrence Carin Chenyang Tao 54 6 0 04 Nov 2021
Improving Model Compatibility of Generative Adversarial Networks by Boundary Calibration Si-An Chen Chun-Liang Li Hsuan-Tien Lin GAN 41 0 0 03 Nov 2021
Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training Minguk Kang Woohyeon Shim Minsu Cho Jaesik Park GAN 100 112 0 01 Nov 2021
Pseudo-Spherical Contrastive Divergence Lantao Yu Jiaming Song Yang Song Stefano Ermon 58 7 0 01 Nov 2021
Estimating and Maximizing Mutual Information for Knowledge Distillation A. Shrivastava Yanjun Qi Vicente Ordonez 56 6 0 29 Oct 2021
OMASGAN: Out-of-Distribution Minimum Anomaly Score GAN for Sample Generation on the Boundary Nikolaos Dionelis Mehrdad Yaghoobi Sotirios A. Tsaftaris OODD 64 6 0 28 Oct 2021
Training Wasserstein GANs without gradient penalties Dohyun Kwon Yeoneung Kim Guido Montúfar Insoon Yang GAN 52 4 0 27 Oct 2021
Analyzing and Improving the Optimization Landscape of Noise-Contrastive Estimation Bingbin Liu Elan Rosenfeld Pradeep Ravikumar Andrej Risteski 57 13 0 21 Oct 2021
A Deep Generative Approach to Conditional Sampling Xingyu Zhou Yuling Jiao Jin Liu Jian Huang 75 43 0 19 Oct 2021
Estimating the Arc Length of the Optimal ROC Curve and Lower Bounding the Maximal AUC Song Liu 36 0 0 18 Oct 2021
Heterogeneous Graph-Based Multimodal Brain Network Learning Gen Shi Yifan Zhu Wenjin Liu Quanming Yao Xia Li 89 8 0 16 Oct 2021
Wasserstein Unsupervised Reinforcement Learning Shuncheng He Yuhang Jiang Hongchang Zhang Jianzhun Shao Xiangyang Ji OffRL 93 24 0 15 Oct 2021
Information Theoretic Structured Generative Modeling Bo Hu Shujian Yu José C. Príncipe SyDa DRL 65 0 0 12 Oct 2021
F-Divergences and Cost Function Locality in Generative Modelling with Quantum Circuits Chiara Leadbeater Louis Sharrock Brian Coyle Marcello Benedetti 59 11 0 08 Oct 2021
Statistical Regeneration Guarantees of the Wasserstein Autoencoder with Latent Space Consistency A. Chakrabarty Swagatam Das DRL 44 6 0 08 Oct 2021
Nonconvex-Nonconcave Min-Max Optimization with a Small Maximization Domain Dmitrii Ostrovskii Babak Barazandeh Meisam Razaviyayn 85 12 0 08 Oct 2021
Pre-training Molecular Graph Representation with 3D Geometry Shengchao Liu Hanchen Wang Weiyang Liu Joan Lasenby Hongyu Guo Jian Tang 201 324 0 07 Oct 2021
InfoSeg: Unsupervised Semantic Image Segmentation with Mutual Information Maximization Robert Harb Patrick Knobelreiter SSL 78 22 0 07 Oct 2021
Score-based Generative Neural Networks for Large-Scale Optimal Transport Max Daniels Tyler Maunu Paul Hand OT DiffM 78 72 0 07 Oct 2021
Reliable Estimation of KL Divergence using a Discriminator in Reproducing Kernel Hilbert Space S. Ghimire A. Masoomi Jennifer Dy 57 8 0 29 Sep 2021
Reversible Gromov-Monge Sampler for Simulation-Based Inference Y. Hur Wenxuan Guo Tengyuan Liang 94 9 0 28 Sep 2021
Variational Disentanglement for Domain Generalization Yufei Wang Haoliang Li Hao Cheng Bihan Wen Lap-Pui Chau Alex C. Kot OOD DRL 122 28 0 13 Sep 2021
Inferential Wasserstein Generative Adversarial Networks Yao Chen Qingyi Gao Xiao Wang GAN 186 23 0 13 Sep 2021
A Novel Intrinsic Measure of Data Separability Shuyue Guan Murray H. Loew 62 18 0 11 Sep 2021
An Empirical Study of Graph Contrastive Learning Yanqiao Zhu Yichen Xu Qiang Liu Shu Wu 97 173 0 02 Sep 2021
Dual Projection Generative Adversarial Networks for Conditional Image Generation Ligong Han Martin Renqiang Min Anastasis Stathopoulos Yu Tian Ruijiang Gao Asim Kadav Dimitris N. Metaxas GAN 87 21 0 20 Aug 2021
Unsupervised Image Generation with Infinite Generative Adversarial Networks Hui Ying He Wang Tianjia Shao Yin Yang Kun Zhou GAN 56 2 0 18 Aug 2021
Toward a `Standard Model' of Machine Learning Zhiting Hu Eric Xing 97 12 0 17 Aug 2021
M2IOSR: Maximal Mutual Information Open Set Recognition Xin Sun Henghui Ding Fangqiu Yi Guosheng Lin K. Ling 81 17 0 05 Aug 2021
Limit Distribution Theory for the Smooth 1-Wasserstein Distance with Applications Ritwik Sadhu Ziv Goldfeld Kengo Kato 79 9 0 28 Jul 2021
AASAE: Augmentation-Augmented Stochastic Autoencoders William Falcon A. Jha Teddy Koker Kyunghyun Cho 102 0 0 26 Jul 2021