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2010.04230
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No MCMC for me: Amortized sampling for fast and stable training of energy-based models
International Conference on Learning Representations (ICLR), 2020
8 October 2020
Will Grathwohl
Jacob Kelly
Milad Hashemi
Mohammad Norouzi
Kevin Swersky
David Duvenaud
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Papers citing
"No MCMC for me: Amortized sampling for fast and stable training of energy-based models"
50 / 62 papers shown
Particle Dynamics for Latent-Variable Energy-Based Models
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Shuxin Zhuang
Rong Feng
Runsheng Yu
Hongzong Li
Youzhi Zhang
181
0
0
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Joint Discriminative-Generative Modeling via Dual Adversarial Training
Xuwang Yin
Claire Zhang
Julie Steele
Nir Shavit
T. T. Wang
GAN
424
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0
13 Oct 2025
Exploring bidirectional bounds for minimax-training of Energy-based models
International Journal of Computer Vision (IJCV), 2025
Cong Geng
Jia Wang
Li Chen
Zhiyong Gao
J. Frellsen
Søren Hauberg
274
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0
05 Jun 2025
Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models
Louis Bethune
David Vigouroux
Yilun Du
Rufin VanRullen
Thomas Serre
Victor Boutin
DiffM
495
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0
23 May 2025
Learning Energy-Based Generative Models via Potential Flow: A Variational Principle Approach to Probability Density Homotopy Matching
Junn Yong Loo
Michelle Adeline
Julia Kaiwen Lau
Fang Yu Leong
Hwa Hui Tew
Arghya Pal
Vishnu Monn Baskaran
Chee-Ming Ting
Raphaël C.-W. Phan
BDL
291
1
0
22 Apr 2025
Learning Energy-Based Models by Self-normalising the Likelihood
Hugo Senetaire
Paul Jeha
Pierre-Alexandre Mattei
J. Frellsen
330
1
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10 Mar 2025
Classification-Denoising Networks
Louis Thiry
Florentin Guth
303
1
0
04 Oct 2024
A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks
International Conference on Machine Learning (ICML), 2024
Nicholas Monath
Will Grathwohl
Michael Boratko
Rob Fergus
Andrew McCallum
Manzil Zaheer
187
0
0
03 Sep 2024
Variational Potential Flow: A Novel Probabilistic Framework for Energy-Based Generative Modelling
Junn Yong Loo
Michelle Adeline
Arghya Pal
Vishnu Monn Baskaran
Chee-Ming Ting
Raphaël C.-W. Phan
DiffM
276
0
0
21 Jul 2024
Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models
Sangwoong Yoon
Himchan Hwang
Dohyun Kwon
Yung-Kyun Noh
Frank C. Park
284
4
0
30 Jun 2024
Lazy Layers to Make Fine-Tuned Diffusion Models More Traceable
Haozhe Liu
Wentian Zhang
Bing Li
Bernard Ghanem
Jürgen Schmidhuber
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WIGM
AAML
269
3
0
01 May 2024
Improving Adversarial Energy-Based Model via Diffusion Process
Cong Geng
Tian Han
Peng-Tao Jiang
Hao Zhang
Jinwei Chen
Søren Hauberg
Yue Liu
DiffM
438
5
0
04 Mar 2024
Learning Energy-based Model via Dual-MCMC Teaching
Neural Information Processing Systems (NeurIPS), 2023
Jiali Cui
Tian Han
232
12
0
05 Dec 2023
Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach
Neural Information Processing Systems (NeurIPS), 2023
Sangwoong Yoon
Young-Uk Jin
Yung-Kyun Noh
Frank C. Park
268
17
0
28 Oct 2023
The Triad of Failure Modes and a Possible Way Out
Emanuele Sansone
211
2
0
27 Sep 2023
Latent Space Energy-based Model for Fine-grained Open Set Recognition
Wentao Bao
Qi Yu
Yu Kong
BDL
371
3
0
19 Sep 2023
Revisiting Energy Based Models as Policies: Ranking Noise Contrastive Estimation and Interpolating Energy Models
Sumeet Singh
Stephen Tu
Vikas Sindhwani
DiffM
284
11
0
11 Sep 2023
Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood
International Conference on Learning Representations (ICLR), 2023
Y. Zhu
Jianwen Xie
Yingnian Wu
Ruiqi Gao
DiffM
684
16
0
10 Sep 2023
Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Models
IEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2023
João Carvalho
An T. Le
Mark Baierl
Dorothea Koert
Jan Peters
DiffM
232
193
0
03 Aug 2023
Training Energy-Based Models with Diffusion Contrastive Divergences
Weijian Luo
Hao Jiang
Tianyang Hu
Jiacheng Sun
Hao Sun
Zhihua Zhang
DiffM
299
8
0
04 Jul 2023
Progressive Energy-Based Cooperative Learning for Multi-Domain Image-to-Image Translation
Weinan Song
Y. Zhu
Lei He
Yingnian Wu
Jianwen Xie
287
1
0
26 Jun 2023
Balanced Training of Energy-Based Models with Adaptive Flow Sampling
Louis Grenioux
Eric Moulines
Marylou Gabrié
350
5
0
01 Jun 2023
Learning Symbolic Representations Through Joint GEnerative and DIscriminative Training
Emanuele Sansone
Robin Manhaeve
BDL
FedML
GAN
285
6
0
22 Apr 2023
Persistently Trained, Diffusion-assisted Energy-based Models
Xinwei Zhang
Z. Tan
Zhijian Ou
DiffM
176
3
0
21 Apr 2023
M-EBM: Towards Understanding the Manifolds of Energy-Based Models
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2023
Xiulong Yang
Shihao Ji
180
6
0
08 Mar 2023
Stabilized training of joint energy-based models and their practical applications
Martin Sustek
Samik Sadhu
L. Burget
H. Hermansky
Jesus Villalba
Laureano Moro-Velazquez
Najim Dehak
AAML
VLM
127
1
0
07 Mar 2023
Guiding Energy-based Models via Contrastive Latent Variables
International Conference on Learning Representations (ICLR), 2023
Hankook Lee
Jongheon Jeong
Sejun Park
Jinwoo Shin
BDL
236
18
0
06 Mar 2023
How to Construct Energy for Images? Denoising Autoencoder Can Be Energy Based Model
W. Zeng
DiffM
195
1
0
05 Mar 2023
Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC
International Conference on Machine Learning (ICML), 2023
Yilun Du
Conor Durkan
Robin Strudel
J. Tenenbaum
Sander Dieleman
Rob Fergus
Jascha Narain Sohl-Dickstein
Arnaud Doucet
Will Grathwohl
DiffM
449
197
0
22 Feb 2023
Versatile Energy-Based Probabilistic Models for High Energy Physics
Neural Information Processing Systems (NeurIPS), 2023
Taoli Cheng
Aaron Courville
DiffM
365
1
0
01 Feb 2023
Learning Data Representations with Joint Diffusion Models
Kamil Deja
Tomasz Trzciñski
Jakub M. Tomczak
DiffM
268
24
0
31 Jan 2023
GEDI: GEnerative and DIscriminative Training for Self-Supervised Learning
Emanuele Sansone
Robin Manhaeve
SSL
429
9
0
27 Dec 2022
Learning Probabilistic Models from Generator Latent Spaces with Hat EBM
Neural Information Processing Systems (NeurIPS), 2022
Mitch Hill
Erik Nijkamp
Jonathan Mitchell
Bo Pang
Song-Chun Zhu
802
13
0
29 Oct 2022
Maximum entropy exploration in contextual bandits with neural networks and energy based models
A. Elwood
Marco Leonardi
A. Mohamed
A. Rozza
198
2
0
12 Oct 2022
Towards Bridging the Performance Gaps of Joint Energy-based Models
Computer Vision and Pattern Recognition (CVPR), 2022
Xiulong Yang
Qing Su
Shihao Ji
VLM
294
18
0
16 Sep 2022
Combating Mode Collapse in GANs via Manifold Entropy Estimation
Haozhe Liu
Bing Li
Haoqian Wu
Hanbang Liang
Yawen Huang
Yuexiang Li
Guohao Li
Yefeng Zheng
GAN
DRL
519
9
0
25 Aug 2022
Your ViT is Secretly a Hybrid Discriminative-Generative Diffusion Model
Xiulong Yang
Sheng-Min Shih
Yinlin Fu
Xiaoting Zhao
Shihao Ji
DiffM
261
62
0
16 Aug 2022
Your Autoregressive Generative Model Can be Better If You Treat It as an Energy-Based One
Yezhen Wang
Tong Che
Yue Liu
Kaitao Song
Hengzhi Pei
Yoshua Bengio
Dongsheng Li
207
5
0
26 Jun 2022
EBM Life Cycle: MCMC Strategies for Synthesis, Defense, and Density Modeling
Mitch Hill
Jonathan Mitchell
Chu Chen
Yuan Du
M. Shah
Song-Chun Zhu
200
0
0
24 May 2022
Learning Energy Networks with Generalized Fenchel-Young Losses
Neural Information Processing Systems (NeurIPS), 2022
Mathieu Blondel
Felipe Llinares-López
Robert Dadashi
Léonard Hussenot
Matthieu Geist
207
9
0
19 May 2022
A Tale of Two Flows: Cooperative Learning of Langevin Flow and Normalizing Flow Toward Energy-Based Model
International Conference on Learning Representations (ICLR), 2022
Jianwen Xie
Y. Zhu
Jilong Li
Ping Li
225
52
0
13 May 2022
Learning Implicit Priors for Motion Optimization
IEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2022
Julen Urain
An T. Le
Alexander Lambert
Georgia Chalvatzaki
Byron Boots
Jan Peters
226
35
0
11 Apr 2022
Bi-level Doubly Variational Learning for Energy-based Latent Variable Models
Computer Vision and Pattern Recognition (CVPR), 2022
Ge Kan
Jinhu Lu
Tian Wang
Baochang Zhang
Aichun Zhu
Lei Huang
Guodong Guo
H. Snoussi
222
8
0
24 Mar 2022
COLD Decoding: Energy-based Constrained Text Generation with Langevin Dynamics
Neural Information Processing Systems (NeurIPS), 2022
Lianhui Qin
Sean Welleck
Daniel Khashabi
Yejin Choi
AI4CE
347
181
0
23 Feb 2022
Energy-Based Contrastive Learning of Visual Representations
Neural Information Processing Systems (NeurIPS), 2022
Beomsu Kim
Jong Chul Ye
238
21
0
10 Feb 2022
Generative Flow Networks for Discrete Probabilistic Modeling
International Conference on Machine Learning (ICML), 2022
Dinghuai Zhang
Nikolay Malkin
Ziqiang Liu
Alexandra Volokhova
Aaron Courville
Yoshua Bengio
309
123
0
03 Feb 2022
Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling
Neural Information Processing Systems (NeurIPS), 2021
Greg Ver Steeg
Aram Galstyan
301
15
0
03 Nov 2021
A Unified View of cGANs with and without Classifiers
Neural Information Processing Systems (NeurIPS), 2021
Si-An Chen
Chun-Liang Li
Hsuan-Tien Lin
GAN
175
12
0
01 Nov 2021
Bounds all around: training energy-based models with bidirectional bounds
Neural Information Processing Systems (NeurIPS), 2021
Cong Geng
Jia Wang
Zhiyong Gao
J. Frellsen
Søren Hauberg
341
17
0
01 Nov 2021
Pseudo-Spherical Contrastive Divergence
Neural Information Processing Systems (NeurIPS), 2021
Lantao Yu
Jiaming Song
Yang Song
Stefano Ermon
222
7
0
01 Nov 2021
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