A Neural Network MCMC sampler that maximizes Proposal Entropy

7 October 2020

Papers citing "A Neural Network MCMC sampler that maximizes Proposal Entropy"

12 / 12 papers shown

Title
Deep Involutive Generative Models for Neural MCMC Span Spanbauer Cameron E. Freer Vikash K. Mansinghka BDL 37 11 0 26 Jun 2020
Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling Tong Che Ruixiang Zhang Jascha Narain Sohl-Dickstein Hugo Larochelle Liam Paull Yuan Cao Yoshua Bengio DiffM DRL 53 113 0 12 Mar 2020
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One Will Grathwohl Kuan-Chieh Wang J. Jacobsen David Duvenaud Mohammad Norouzi Kevin Swersky VLM 74 536 0 06 Dec 2019
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 139 1,662 0 05 Dec 2019
Gradient-based Adaptive Markov Chain Monte Carlo Michalis K. Titsias P. Dellaportas BDL 70 22 0 04 Nov 2019
Normalizing Flows: An Introduction and Review of Current Methods I. Kobyzev S. Prince Marcus A. Brubaker TPM MedIm 39 57 0 25 Aug 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 42 154 0 29 Mar 2019
Ergodic Inference: Accelerate Convergence by Optimisation Yichuan Zhang José Miguel Hernández-Lobato BDL 48 9 0 25 May 2018
Generalizing Hamiltonian Monte Carlo with Neural Networks Daniel Levy Matthew D. Hoffman Jascha Narain Sohl-Dickstein BDL 51 130 0 25 Nov 2017
A-NICE-MC: Adversarial Training for MCMC Jiaming Song Shengjia Zhao Stefano Ermon BDL OOD 63 109 0 23 Jun 2017
Faster Eigenvector Computation via Shift-and-Invert Preconditioning Dan Garber Laurent Dinh Chi Jin Jascha Narain Sohl-Dickstein Samy Bengio Praneeth Netrapalli Aaron Sidford 185 3,681 0 26 May 2016
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo Matthew D. Hoffman Andrew Gelman 139 4,275 0 18 Nov 2011