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

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

2 June 2016
Sebastian Nowozin
Botond Cseke
Ryota Tomioka
    GAN
ArXiv (abs)PDFHTML

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
AI4CEVLM
30
0
0
10 Jun 2025
Generalization in VAE and Diffusion Models: A Unified Information-Theoretic Analysis
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
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
Joint-stochastic-approximation Autoencoders with Application to Semi-supervised Learning
Wenbo He
Zhijian Ou
DRLBDL
40
0
0
24 May 2025
$α$-GAN by Rényi Cross Entropy
ααα-GAN by Rényi Cross Entropy
Ni Ding
Miao Qiao
Jiaxing Xu
Yiping Ke
Xiaoyu Zhang
GAN
59
0
0
20 May 2025
Proximal optimal transport divergences
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
Bounding Neyman-Pearson Region with fff-Divergences
Andrew Mullhaupt
Cheng Peng
47
0
0
13 May 2025
ADD: Physics-Based Motion Imitation with Adversarial Differential Discriminators
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
fff-PO: Generalizing Preference Optimization with fff-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
Robust Estimation for Kernel Exponential Families with Smoothed Total Variation Distances
Takafumi Kanamori
Kodai Yokoyama
Takayuki Kawashima
28
0
0
28 Oct 2024
Kernel Approximation of Fisher-Rao Gradient Flows
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
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
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
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
KELMMU
165
20
0
14 Oct 2024
A Benchmark Suite for Evaluating Neural Mutual Information Estimators on
  Unstructured Datasets
A Benchmark Suite for Evaluating Neural Mutual Information Estimators on Unstructured Datasets
Kyungeun Lee
Wonjong Rhee
79
5
0
14 Oct 2024
Beyond Squared Error: Exploring Loss Design for Enhanced Training of
  Generative Flow Networks
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
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
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
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
Generalizing Alignment Paradigm of Text-to-Image Generation with Preferences through fff-divergence Minimization
Haoyuan Sun
Bo Xia
Yongzhe Chang
Xueqian Wang
EGVM
67
6
0
15 Sep 2024
Disentangled Noisy Correspondence Learning
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
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
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
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
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
ALMKELM
103
32
0
02 Jul 2024
Coding for Intelligence from the Perspective of Category
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
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
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
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
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
Causal Contrastive Learning for Counterfactual Regression Over Time
Mouad El Bouchattaoui
Myriam Tami
Benoit Lepetit
P. Cournède
CMLAI4TS
87
3
0
01 Jun 2024
MCGAN: Enhancing GAN Training with Regression-Based Generator Loss
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
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
Learning heavy-tailed distributions with Wasserstein-proximal-regularized ααα-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
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
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