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"

50 / 904 papers shown

Title
Graph Prompting for Graph Learning Models: Recent Advances and Future Directions Xingbo Fu Zehong Wang Zihan Chen Jiazheng Li Yaochen Zhu Zhenyu Lei Cong Shen Yanfang Ye Chuxu Zhang Jundong Li AI4CE VLM 30 0 0 10 Jun 2025
Generalization in VAE and Diffusion Models: A Unified Information-Theoretic Analysis Qi Chen Jierui Zhu Florian Shkurti DiffM 72 1 0 01 Jun 2025
AMOR: Adaptive Character Control through Multi-Objective Reinforcement Learning Lucas N. Alegre Agon Serifi Ruben Grandia David Müller Espen Knoop Moritz Bächer 60 0 0 29 May 2025
Joint-stochastic-approximation Autoencoders with Application to Semi-supervised Learning Wenbo He Zhijian Ou DRL BDL 40 0 0 24 May 2025
$α$ -GAN by Rényi Cross Entropy Ni Ding Miao Qiao Jiaxing Xu Yiping Ke Xiaoyu Zhang GAN 57 0 0 20 May 2025
Proximal optimal transport divergences Ricardo Baptista Panagiota Birmpa Markos A. Katsoulakis Luc Rey-Bellet Benjamin J. Zhang OT 100 0 0 17 May 2025
Bounding Neyman-Pearson Region with $f$ -Divergences Andrew Mullhaupt Cheng Peng 47 0 0 13 May 2025
ADD: Physics-Based Motion Imitation with Adversarial Differential Discriminators Ziyu Zhang S. Bashkirov Dun Yang Michael Taylor Xue Bin Peng 88 0 0 08 May 2025
Boosting Statistic Learning with Synthetic Data from Pretrained Large Models Jialong Jiang Wenkang Hu Jian Huang Yuling Jiao Xu Liu DiffM 89 0 0 08 May 2025
Benchmarking Mutual Information-based Loss Functions in Federated Learning Sarang S Harsh D. Chothani Qilei Li A. Abdelmoniem Arnab K. Paul FedML 65 0 0 16 Apr 2025
Robust Classification with Noisy Labels Based on Posterior Maximization Nicola Novello Andrea M. Tonello NoLa 97 0 0 09 Apr 2025
CKGAN: Training Generative Adversarial Networks Using Characteristic Kernel Integral Probability Metrics Kuntian Zhang Simin Yu Yaoshu Wang Makoto Onizuka Chuan Xiao GAN 98 0 0 08 Apr 2025
Improving Discriminator Guidance in Diffusion Models Alexandre Verine Mehdi Inane Florian Le Bronnec Benjamin Négrevergne Y. Chevaleyre DiffM 115 0 0 20 Mar 2025
Graph-Weighted Contrastive Learning for Semi-Supervised Hyperspectral Image Classification Yuqing Zhang Qi Han Ligeng Wang Kai Cheng Bo Wang Kun Zhan 85 0 0 19 Mar 2025
A Deep Bayesian Nonparametric Framework for Robust Mutual Information Estimation Forough Fazeliasl Michael Minyi Zhang Bei Jiang Linglong Kong 85 0 0 13 Mar 2025
Text-to-3D Generation using Jensen-Shannon Score Distillation Khoi Do Binh-Son Hua DiffM 94 0 0 08 Mar 2025
A Fused Gromov-Wasserstein Approach to Subgraph Contrastive Learning Amadou S. Sangare Nicolas Dunou Jhony H. Giraldo Fragkiskos D. Malliaros SSL 129 1 0 28 Feb 2025
INFO-SEDD: Continuous Time Markov Chains as Scalable Information Metrics Estimators Alberto Foresti Giulio Franzese Pietro Michiardi 144 0 0 26 Feb 2025
Inverse-RLignment: Large Language Model Alignment from Demonstrations through Inverse Reinforcement Learning Hao Sun M. Schaar 182 18 0 28 Jan 2025
Nested Annealed Training Scheme for Generative Adversarial Networks Chang Wan Ming-Hsuan Yang Minglu Li Yunliang Jiang Zhonglong Zheng GAN 131 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 242 0 0 17 Jan 2025
Learning Robust and Privacy-Preserving Representations via Information Theory Binghui Zhang Sayedeh Leila Noorbakhsh Yun Dong Yuan Hong Binghui Wang 159 0 0 15 Dec 2024
Negative-Free Self-Supervised Gaussian Embedding of Graphs Yunhui Liu Tieke He Tao Zheng Jianhua Zhao SSL 91 2 0 02 Nov 2024
$f$ -PO: Generalizing Preference Optimization with $f$ -divergence Minimization Jiaqi Han Mingjian Jiang Yuxuan Song J. Leskovec Stefano Ermon 123 6 0 29 Oct 2024
Robust Estimation for Kernel Exponential Families with Smoothed Total Variation Distances Takafumi Kanamori Kodai Yokoyama Takayuki Kawashima 26 0 0 28 Oct 2024
Kernel Approximation of Fisher-Rao Gradient Flows Jia Jie Zhu Alexander Mielke 157 6 0 27 Oct 2024
Privacy without Noisy Gradients: Slicing Mechanism for Generative Model Training Kristjan Greenewald Yuancheng Yu Hao Wang Kai Xu 142 2 0 25 Oct 2024
LLM-TS Integrator: Integrating LLM for Enhanced Time Series Modeling Can Chen Gabriel Oliveira Hossein Sharifi-Noghabi Tristan Sylvain AI4TS 54 2 0 21 Oct 2024
LLM Unlearning via Loss Adjustment with Only Forget Data Yaxuan Wang Jiaheng Wei Chris Yuhao Liu Jinlong Pang Qiang Liu A. Shah Yujia Bao Yang Liu Wei Wei KELM MU 165 20 0 14 Oct 2024
A Benchmark Suite for Evaluating Neural Mutual Information Estimators on Unstructured Datasets Kyungeun Lee Wonjong Rhee 77 5 0 14 Oct 2024
Beyond Squared Error: Exploring Loss Design for Enhanced Training of Generative Flow Networks Rui Hu Yifan Zhang Zhuoran Li Longbo Huang 101 2 0 03 Oct 2024
Bounds on Lp errors in density ratio estimation via f-divergence loss functions Yoshiaki Kitazawa 113 1 0 02 Oct 2024
CF-GO-Net: A Universal Distribution Learner via Characteristic Function Networks with Graph Optimizers Zeyang Yu Shengxi Li Danilo Mandic OOD 32 0 0 19 Sep 2024
A Simpler Alternative to Variational Regularized Counterfactual Risk Minimization Hua Chang Bakker Shashank Gupta Harrie Oosterhuis OffRL 59 0 0 15 Sep 2024
Generalizing Alignment Paradigm of Text-to-Image Generation with Preferences through $f$ -divergence Minimization Haoyuan Sun Bo Xia Yongzhe Chang Xueqian Wang EGVM 67 6 0 15 Sep 2024
Disentangled Noisy Correspondence Learning Zhuohang Dang Minnan Luo Jihong Wang Chengyou Jia Haochen Han Herun Wan Guang Dai Xiaojun Chang Jingdong Wang 98 1 0 10 Aug 2024
Bootstrap Latents of Nodes and Neighbors for Graph Self-Supervised Learning Yunhui Liu Huaisong Zhang Tieke He Tao Zheng Jianhua Zhao SSL 84 6 0 09 Aug 2024
HiLo: A Learning Framework for Generalized Category Discovery Robust to Domain Shifts Hongjun Wang S. Vaze Kai Han 166 5 0 08 Aug 2024
Time Series Generative Learning with Application to Brain Imaging Analysis Zhenghao Li Sanyou Wu Long Feng MedIm 94 0 0 19 Jul 2024
Survey on Knowledge Distillation for Large Language Models: Methods, Evaluation, and Application Chuanpeng Yang Wang Lu Yao Zhu Yidong Wang Qian Chen Chenlong Gao Bingjie Yan Yiqiang Chen ALM KELM 103 32 0 02 Jul 2024
Coding for Intelligence from the Perspective of Category Wenhan Yang Zixuan Hu Lilang Lin Jiaying Liu Ling-Yu Duan AI4CE 174 1 0 01 Jul 2024
Kolmogorov-Smirnov GAN Maciej Falkiewicz Naoya Takeishi Alexandros Kalousis GAN 57 0 0 28 Jun 2024
InfoGaussian: Structure-Aware Dynamic Gaussians through Lightweight Information Shaping Yunchao Zhang Guandao Yang Leonidas Guibas Yanchao Yang 3DGS 90 1 0 09 Jun 2024
Logical Reasoning with Relation Network for Inductive Knowledge Graph Completion Qinggang Zhang Keyu Duan Junnan Dong Pai Zheng Xiao Huang 114 3 0 03 Jun 2024
An Information Compensation Framework for Zero-Shot Skeleton-based Action Recognition Haojun Xu Yanlei Gao Jie Li Xinbo Gao 80 2 0 02 Jun 2024
Causal Contrastive Learning for Counterfactual Regression Over Time Mouad El Bouchattaoui Myriam Tami Benoit Lepetit P. Cournède CML AI4TS 87 3 0 01 Jun 2024
MCGAN: Enhancing GAN Training with Regression-Based Generator Loss Baoren Xiao Hao Ni Weixin Yang GAN 156 0 0 27 May 2024
Defining error accumulation in ML atmospheric simulators R. Parthipan Mohit Anand Hannah M. Christensen J. S. Hosking Damon J. Wischik 41 1 0 23 May 2024
Learning heavy-tailed distributions with Wasserstein-proximal-regularized $α$ -divergences Ziyu Chen Hyemin Gu Markos A. Katsoulakis Luc Rey-Bellet Wei-wei Zhu 99 1 0 22 May 2024
Semantic Loss Functions for Neuro-Symbolic Structured Prediction Kareem Ahmed Stefano Teso Paolo Morettin Luca Di Liello Pierfrancesco Ardino ... Yitao Liang Eric Wang Kai-Wei Chang Andrea Passerini Guy Van den Broeck 95 3 0 12 May 2024