On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models

29 March 2019

Erik Nijkamp

Papers citing "On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models"

26 / 26 papers shown

Title
Discrete Neural Flow Samplers with Locally Equivariant Transformer Zijing Ou Ruixiang Zhang Yingzhen Li 52 0 0 23 May 2025
Diffusion at Absolute Zero: Langevin Sampling Using Successive Moreau Envelopes [conference paper] Andreas Habring Alexander Falk Thomas Pock 84 0 0 03 Feb 2025
Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Probabilistic Interpretations Xin-Chao Xu Yi Qin Lu Mi Hao Wang Xuelong Li 101 12 0 03 Jan 2025
Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Model Erik Nijkamp Mitch Hill Song-Chun Zhu Ying Nian Wu 79 212 0 22 Apr 2019
Implicit Generation and Generalization in Energy-Based Models Yilun Du Igor Mordatch BDL DiffM 55 40 0 20 Mar 2019
Maximum Entropy Generators for Energy-Based Models Rithesh Kumar Sherjil Ozair Anirudh Goyal Aaron Courville Yoshua Bengio 44 113 0 24 Jan 2019
Divergence Triangle for Joint Training of Generator Model, Energy-based Model, and Inference Model Tian Han Erik Nijkamp Xiaolin Fang Mitch Hill Song-Chun Zhu Ying Nian Wu 67 68 0 28 Dec 2018
On the Spectral Bias of Neural Networks Nasim Rahaman A. Baratin Devansh Arpit Felix Dräxler Min Lin Fred Hamprecht Yoshua Bengio Aaron Courville 135 1,438 0 22 Jun 2018
Learning Descriptor Networks for 3D Shape Synthesis and Analysis Jianwen Xie Zilong Zheng Ruiqi Gao Wenguan Wang Song-Chun Zhu Ying Nian Wu GAN 3DV 61 145 0 02 Apr 2018
Building a Telescope to Look Into High-Dimensional Image Spaces Mitch Hill Erik Nijkamp Song-Chun Zhu DiffM 52 10 0 02 Mar 2018
Spectral Normalization for Generative Adversarial Networks Takeru Miyato Toshiki Kataoka Masanori Koyama Yuichi Yoshida ODL 155 4,437 0 16 Feb 2018
Wasserstein Introspective Neural Networks Kwonjoon Lee Weijian Xu Fan Fan Zhuowen Tu 70 57 0 24 Nov 2017
Non-local Neural Networks Xinyu Wang Ross B. Girshick Abhinav Gupta Kaiming He OffRL 283 8,905 0 21 Nov 2017
Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net Anirudh Goyal Nan Rosemary Ke Surya Ganguli Yoshua Bengio DiffM 119 55 0 07 Nov 2017
Learning Energy-Based Models as Generative ConvNets via Multi-grid Modeling and Sampling Ruiqi Gao Yang Lu Junpei Zhou Song-Chun Zhu Ying Nian Wu 74 79 0 26 Sep 2017
Calibrating Energy-based Generative Adversarial Networks Zihang Dai Amjad Almahairi Philip Bachman Eduard H. Hovy Aaron Courville GAN 53 111 0 06 Feb 2017
Cooperative Training of Descriptor and Generator Networks Jianwen Xie Yang Lu Ruiqi Gao Song-Chun Zhu Ying Nian Wu GAN 55 143 0 29 Sep 2016
Deep Directed Generative Models with Energy-Based Probability Estimation Taesup Kim Yoshua Bengio GAN 45 136 0 10 Jun 2016
The Latin American Giant Observatory: a successful collaboration in Latin America based on Cosmic Rays and computer science domains Hernán Asorey R. Mayo-García L. Núñez M. Pascual A. J. Rubio-Montero M. Suárez-Durán L. A. Torres-Niño 81 5 0 30 May 2016
A Theory of Generative ConvNet Jianwen Xie Yang Lu Song-Chun Zhu Ying Nian Wu DiffM GAN 86 320 0 10 Feb 2016
Visualizing Deep Convolutional Neural Networks Using Natural Pre-Images Aravindh Mahendran Andrea Vedaldi FAtt 68 534 0 07 Dec 2015
Learning FRAME Models Using CNN Filters Yang Lu Song-Chun Zhu Ying Nian Wu GAN 51 66 0 28 Sep 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.8K 150,039 0 22 Dec 2014
Generative Modeling of Convolutional Neural Networks Jifeng Dai Ying Nian Wu Ying-Nian Wu 58 75 0 19 Dec 2014
Stochastic Gradient Hamiltonian Monte Carlo Tianqi Chen E. Fox Carlos Guestrin BDL 106 908 0 17 Feb 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 447 16,940 0 20 Dec 2013