Generative Modeling by Inclusive Neural Random Fields with Applications
in Image Generation and Anomaly Detection

Generative Modeling by Inclusive Neural Random Fields with Applications in Image Generation and Anomaly Detection

1 June 2018

Zhijian Ou

Papers citing "Generative Modeling by Inclusive Neural Random Fields with Applications in Image Generation and Anomaly Detection"

11 / 11 papers shown

Title
Constraining Pseudo-label in Self-training Unsupervised Domain Adaptation with Energy-based Model Lingsheng Kong Bo Hu Xiongchang Liu Jun Lu Jane You Xiaofeng Liu 31 12 0 26 Aug 2022
Learning to Compose Visual Relations Nan Liu Shuang Li Yilun Du J. Tenenbaum Antonio Torralba CoGe OCL 32 77 0 17 Nov 2021
Unsupervised Learning of Compositional Energy Concepts Yilun Du Shuang Li Yash Sharma J. Tenenbaum Igor Mordatch CoGe OCL 30 76 0 04 Nov 2021
Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling Greg Ver Steeg Aram Galstyan 41 13 0 03 Nov 2021
Energy-constrained Self-training for Unsupervised Domain Adaptation Xiaofeng Liu Bo Hu Xiongchang Liu Jun Lu J. You Lingsheng Kong 44 29 0 01 Jan 2021
Improved Contrastive Divergence Training of Energy Based Models Yilun Du Shuang Li J. Tenenbaum Igor Mordatch 41 138 0 02 Dec 2020
Online Safety Assurance for Deep Reinforcement Learning Noga H. Rotman Michael Schapira Aviv Tamar OffRL 36 5 0 07 Oct 2020
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One Will Grathwohl Kuan-Chieh Jackson Wang J. Jacobsen David Duvenaud Mohammad Norouzi Kevin Swersky VLM 43 527 0 06 Dec 2019
A Review of Learning with Deep Generative Models from Perspective of Graphical Modeling Zhijian Ou 31 16 0 05 Aug 2018
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results Antti Tarvainen Harri Valpola OOD MoMe 267 1,275 0 06 Mar 2017
MCMC using Hamiltonian dynamics Radford M. Neal 185 3,267 0 09 Jun 2012