Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Model

22 April 2019

Erik Nijkamp

Papers citing "Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Model"

39 / 39 papers shown

Title
Bayesian Computation in Deep Learning Wenlong Chen Bolian Li Ruqi Zhang Yingzhen Li BDL 75 0 0 25 Feb 2025
LSEBMCL: A Latent Space Energy-Based Model for Continual Learning Xiaodi Li Dingcheng Li Rujun Gao Mahmoud Zamani Latifur Khan CLL KELM 42 0 0 09 Jan 2025
Provable Convergence and Limitations of Geometric Tempering for Langevin Dynamics Omar Chehab Anna Korba Austin Stromme Adrien Vacher 33 2 0 13 Oct 2024
EQ-CBM: A Probabilistic Concept Bottleneck with Energy-based Models and Quantized Vectors Sangwon Kim Dasom Ahn B. Ko In-su Jang Kwang-Ju Kim 20 4 0 22 Sep 2024
Latent Space Energy-based Neural ODEs Sheng Cheng Deqian Kong Jianwen Xie Kookjin Lee Ying Nian Wu Yezhou Yang DiffM 111 1 0 05 Sep 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 22 3 0 30 Jun 2024
Cascade of phase transitions in the training of Energy-based models Dimitrios Bachtis Giulio Biroli A. Decelle Beatriz Seoane 34 4 0 23 May 2024
Generative modeling through internal high-dimensional chaotic activity Samantha J. Fournier Pierfrancesco Urbani 27 1 0 17 May 2024
TEA: Test-time Energy Adaptation Yige Yuan Bingbing Xu Liang Hou Fei Sun Huawei Shen Xueqi Cheng TTA VLM 26 7 0 24 Nov 2023
Balanced Training of Energy-Based Models with Adaptive Flow Sampling Louis Grenioux Eric Moulines Marylou Gabrié 13 2 0 01 Jun 2023
Moment Matching Denoising Gibbs Sampling Mingtian Zhang Alex Hawkins-Hooker Brooks Paige David Barber DiffM 24 3 0 19 May 2023
Likelihood-Based Generative Radiance Field with Latent Space Energy-Based Model for 3D-Aware Disentangled Image Representation Y. Zhu Jianwen Xie Ping Li MedIm 20 4 0 16 Apr 2023
Non-Generative Energy Based Models Jacob Piland Christopher Sweet Priscila Saboia Charles Vardeman A. Czajka 28 0 0 03 Apr 2023
AdaptDiffuser: Diffusion Models as Adaptive Self-evolving Planners Zhixuan Liang Yao Mu Mingyu Ding Fei Ni M. Tomizuka Ping Luo 64 99 0 03 Feb 2023
Explaining the effects of non-convergent sampling in the training of Energy-Based Models E. Agoritsas Giovanni Catania A. Decelle Beatriz Seoane DiffM 14 10 0 23 Jan 2023
A Tale of Two Latent Flows: Learning Latent Space Normalizing Flow with Short-run Langevin Flow for Approximate Inference Jianwen Xie Y. Zhu Yifei Xu Dingcheng Li Ping Li BDL DRL 12 7 0 23 Jan 2023
GEDI: GEnerative and DIscriminative Training for Self-Supervised Learning Emanuele Sansone Robin Manhaeve SSL 15 9 0 27 Dec 2022
Robust Graph Representation Learning via Predictive Coding Billy Byiringiro Tommaso Salvatori Thomas Lukasiewicz OOD 23 6 0 09 Dec 2022
Is Conditional Generative Modeling all you need for Decision-Making? Anurag Ajay Yilun Du Abhi Gupta J. Tenenbaum Tommi Jaakkola Pulkit Agrawal DiffM 39 359 0 28 Nov 2022
A Tale of Two Flows: Cooperative Learning of Langevin Flow and Normalizing Flow Toward Energy-Based Model Jianwen Xie Y. Zhu J. Li Ping Li 16 50 0 13 May 2022
Learning Generative Vision Transformer with Energy-Based Latent Space for Saliency Prediction Jing Zhang Jianwen Xie Nick Barnes Ping Li ViT 35 90 0 27 Dec 2021
Path Integral Sampler: a stochastic control approach for sampling Qinsheng Zhang Yongxin Chen DiffM 13 101 0 30 Nov 2021
Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling Greg Ver Steeg Aram Galstyan 28 13 0 03 Nov 2021
Unsupervised Foreground Extraction via Deep Region Competition Peiyu Yu Sirui Xie Xiaojian Ma Yixin Zhu Ying Nian Wu Song-Chun Zhu OCL 24 42 0 29 Oct 2021
LEO: Learning Energy-based Models in Factor Graph Optimization Paloma Sodhi Eric Dexheimer Mustafa Mukadam Stuart Anderson Michael Kaess 32 16 0 04 Aug 2021
Directly Training Joint Energy-Based Models for Conditional Synthesis and Calibrated Prediction of Multi-Attribute Data Jacob Kelly R. Zemel Will Grathwohl 31 2 0 19 Jul 2021
Autoencoding Under Normalization Constraints Sangwoong Yoon Yung-Kyun Noh Frank C. Park OODD UQCV 25 38 0 12 May 2021
3D Shape Generation and Completion through Point-Voxel Diffusion Linqi Zhou Yilun Du Jiajun Wu DiffM 24 510 0 08 Apr 2021
Deep Consensus Learning Wei Sun Tianfu Wu 24 2 0 15 Mar 2021
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models Sam Bond-Taylor Adam Leach Yang Long Chris G. Willcocks VLM TPM 36 478 0 08 Mar 2021
How to Train Your Energy-Based Models Yang Song Diederik P. Kingma DiffM 8 241 0 09 Jan 2021
Learning Energy-Based Models With Adversarial Training Xuwang Yin Shiying Li Gustavo K. Rohde AAML DiffM 12 9 0 11 Dec 2020
Accurate 3D Object Detection using Energy-Based Models Fredrik K. Gustafsson Martin Danelljan Thomas B. Schon 3DPC 30 10 0 08 Dec 2020
Improved Contrastive Divergence Training of Energy Based Models Yilun Du Shuang Li J. Tenenbaum Igor Mordatch 14 138 0 02 Dec 2020
Locally Masked Convolution for Autoregressive Models Ajay Jain Pieter Abbeel Deepak Pathak DiffM OffRL 28 31 0 22 Jun 2020
Denoising Diffusion Probabilistic Models Jonathan Ho Ajay Jain Pieter Abbeel DiffM 116 16,901 0 19 Jun 2020
Residual Energy-Based Models for Text Generation Yuntian Deng A. Bakhtin Myle Ott Arthur Szlam MarcÁurelio Ranzato 20 125 0 22 Apr 2020
Learning Multi-layer Latent Variable Model via Variational Optimization of Short Run MCMC for Approximate Inference Erik Nijkamp Bo Pang Tian Han Linqi Zhou Song-Chun Zhu Ying Nian Wu BDL DRL 17 2 0 04 Dec 2019
On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models Erik Nijkamp Mitch Hill Tian Han Song-Chun Zhu Ying Nian Wu 19 151 0 29 Mar 2019