A Theory of Generative ConvNet

10 February 2016

Papers citing "A Theory of Generative ConvNet"

50 / 221 papers shown

Title
Accurate 3D Object Detection using Energy-Based Models Fredrik K. Gustafsson Martin Danelljan Thomas B. Schon 3DPC 30 10 0 08 Dec 2020
Contrastive Divergence Learning is a Time Reversal Adversarial Game Omer Yair T. Michaeli GAN 10 6 0 06 Dec 2020
Improved Contrastive Divergence Training of Energy Based Models Yilun Du Shuang Li J. Tenenbaum Igor Mordatch 16 138 0 02 Dec 2020
Unpaired Image-to-Image Translation via Latent Energy Transport Yang Zhao Changyou Chen 4 27 0 01 Dec 2020
Energy-Based Models for Continual Learning Shuang Li Yilun Du Gido M. van de Ven Igor Mordatch 19 42 0 24 Nov 2020
Dual Contradistinctive Generative Autoencoder Gaurav Parmar Dacheng Li Kwonjoon Lee Z. Tu GAN 17 81 0 19 Nov 2020
An empirical study of domain-agnostic semi-supervised learning via energy-based models: joint-training and pre-training Yunfu Song Huahuan Zheng Zhijian Ou 12 0 0 25 Oct 2020
Semi-supervised Learning by Latent Space Energy-Based Model of Symbol-Vector Coupling Bo Pang Erik Nijkamp Jiali Cui Tian Han Ying Nian Wu SSL 27 4 0 19 Oct 2020
Set Prediction without Imposing Structure as Conditional Density Estimation David W. Zhang Gertjan J. Burghouts Cees G. M. Snoek 43 17 0 08 Oct 2020
Energy-based Out-of-distribution Detection Weitang Liu Xiaoyun Wang John Douglas Owens Yixuan Li OODD 42 1,291 0 08 Oct 2020
A Neural Network MCMC sampler that maximizes Proposal Entropy Zengyi Li Yubei Chen Friedrich T. Sommer 25 14 0 07 Oct 2020
VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models Zhisheng Xiao Karsten Kreis Jan Kautz Arash Vahdat 11 123 0 01 Oct 2020
Hybrid Discriminative-Generative Training via Contrastive Learning Hao Liu Pieter Abbeel SSL 15 40 0 17 Jul 2020
Efficient Learning of Generative Models via Finite-Difference Score Matching Tianyu Pang Kun Xu Chongxuan Li Yang Song Stefano Ermon Jun Zhu DiffM 22 53 0 07 Jul 2020
Strictly Batch Imitation Learning by Energy-based Distribution Matching Daniel Jarrett Ioana Bica M. Schaar OffRL 11 62 0 25 Jun 2020
Denoising Diffusion Probabilistic Models Jonathan Ho Ajay Jain Pieter Abbeel DiffM 116 16,901 0 19 Jun 2020
MCMC Should Mix: Learning Energy-Based Model with Neural Transport Latent Space MCMC Erik Nijkamp Ruiqi Gao Pavel Sountsov Srinivas Vasudevan Bo Pang Song-Chun Zhu Ying Nian Wu BDL 8 20 0 12 Jun 2020
Stochastic Security: Adversarial Defense Using Long-Run Dynamics of Energy-Based Models Mitch Hill Jonathan Mitchell Song-Chun Zhu AAML 11 68 0 27 May 2020
How to Train Your Energy-Based Model for Regression Fredrik K. Gustafsson Martin Danelljan Radu Timofte Thomas B. Schon 37 42 0 04 May 2020
Residual Energy-Based Models for Text Generation Yuntian Deng A. Bakhtin Myle Ott Arthur Szlam MarcÁurelio Ranzato 20 125 0 22 Apr 2020
Compositional Visual Generation and Inference with Energy Based Models Yilun Du Shuang Li Igor Mordatch CoGe 12 23 0 13 Apr 2020
Residual Energy-Based Models for Text A. Bakhtin Yuntian Deng Sam Gross Myle Ott MarcÁurelio Ranzato Arthur Szlam 19 13 0 06 Apr 2020
Generative PointNet: Deep Energy-Based Learning on Unordered Point Sets for 3D Generation, Reconstruction and Classification Jianwen Xie Yifei Xu Zilong Zheng Song-Chun Zhu Ying Nian Wu 3DPC 16 79 0 02 Apr 2020
Energy-Based Processes for Exchangeable Data Mengjiao Yang Bo Dai H. Dai Dale Schuurmans 4 12 0 17 Mar 2020
Generalized Energy Based Models Michael Arbel Liang Zhou A. Gretton DRL 17 78 0 10 Mar 2020
Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling Will Grathwohl Kuan-Chieh Jackson Wang J. Jacobsen D. Duvenaud R. Zemel 11 14 0 13 Feb 2020
Conditional Generative ConvNets for Exemplar-based Texture Synthesis Zifeng Wang Menghan Li Guisong Xia 8 12 0 17 Dec 2019
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One Will Grathwohl Kuan-Chieh Jackson Wang J. Jacobsen D. Duvenaud Mohammad Norouzi Kevin Swersky VLM 20 527 0 06 Dec 2019
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
Flow Contrastive Estimation of Energy-Based Models Ruiqi Gao Erik Nijkamp Diederik P. Kingma Zhen Xu Andrew M. Dai Ying Nian Wu GAN 14 111 0 02 Dec 2019
Learning Perceptual Inference by Contrasting Chi Zhang Baoxiong Jia Feng Gao Yixin Zhu Hongjing Lu Song-Chun Zhu LRM 10 107 0 29 Nov 2019
Representation Learning: A Statistical Perspective Jianwen Xie Ruiqi Gao Erik Nijkamp Song-Chun Zhu Ying Nian Wu SSL 11 12 0 26 Nov 2019
Motion-Based Generator Model: Unsupervised Disentanglement of Appearance, Trackable and Intrackable Motions in Dynamic Patterns Jianwen Xie Ruiqi Gao Zilong Zheng Song-Chun Zhu Ying Nian Wu DiffM 19 21 0 26 Nov 2019
Energy-Inspired Models: Learning with Sampler-Induced Distributions Dieterich Lawson George Tucker Bo Dai Rajesh Ranganath 11 31 0 31 Oct 2019
A Near-Optimal Gradient Flow for Learning Neural Energy-Based Models Yang Wu Pengxu Wei Liang Lin 12 0 0 31 Oct 2019
Meta-Learning Deep Energy-Based Memory Models Sergey Bartunov Jack W. Rae Simon Osindero Timothy Lillicrap 24 34 0 07 Oct 2019
Bridging Explicit and Implicit Deep Generative Models via Neural Stein Estimators Qitian Wu Rui Gao H. Zha GAN 6 5 0 28 Sep 2019
Learning Energy-based Spatial-Temporal Generative ConvNets for Dynamic Patterns Jianwen Xie Song-Chun Zhu Ying Nian Wu GAN 27 52 0 26 Sep 2019
Convolutional Bipartite Attractor Networks Michael L. Iuzzolino Y. Singer Michael C. Mozer 9 8 0 08 Jun 2019
Learning Feature-to-Feature Translator by Alternating Back-Propagation for Generative Zero-Shot Learning Yizhe Zhu Jianwen Xie Bingchen Liu Ahmed Elgammal VLM 13 86 0 22 Apr 2019
Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Model Erik Nijkamp Mitch Hill Song-Chun Zhu Ying Nian Wu 29 208 0 22 Apr 2019
Energy-Based Continuous Inverse Optimal Control Yifei Xu Jianwen Xie Tianyang Zhao Chris L. Baker Yibiao Zhao Ying Nian Wu 17 19 0 10 Apr 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
Implicit Generation and Generalization in Energy-Based Models Yilun Du Igor Mordatch BDL DiffM 19 40 0 20 Mar 2019
Cooperative Training of Fast Thinking Initializer and Slow Thinking Solver for Conditional Learning Jianwen Xie Zilong Zheng Xiaolin Fang Song-Chun Zhu Ying Nian Wu 18 4 0 07 Feb 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 34 67 0 28 Dec 2018
FRAME Revisited: An Interpretation View Based on Particle Evolution Xu Cai Yang Wu Guanbin Li Ziliang Chen Liang Lin 11 2 0 04 Dec 2018
A Tale of Three Probabilistic Families: Discriminative, Descriptive and Generative Models Ying Nian Wu Ruiqi Gao Tian Han Song-Chun Zhu TPM 31 17 0 09 Oct 2018
Estimation of Non-Normalized Mixture Models and Clustering Using Deep Representation Takeru Matsuda Aapo Hyvarinen 10 2 0 19 May 2018
Image Generation from Scene Graphs Justin Johnson Agrim Gupta Li Fei-Fei GNN 223 815 0 04 Apr 2018