Hamiltonian Generative Networks

30 September 2019

Peter Toth

Danilo Jimenez Rezende

Papers citing "Hamiltonian Generative Networks"

21 / 21 papers shown

Title
Learning Physics From Video: Unsupervised Physical Parameter Estimation for Continuous Dynamical Systems Alejandro Castañeda Garcia Jan van Gemert Daan Brinks Nergis Tömen 52 0 0 02 Oct 2024
Learning Generalized Hamiltonians using fully Symplectic Mappings Harsh Choudhary Chandan Gupta Vyacheslav kungrutsev Melvin Leok Georgios Korpas 45 0 0 17 Sep 2024
Residual Flows for Invertible Generative Modeling Ricky T. Q. Chen Jens Behrmann David Duvenaud J. Jacobsen BDL TPM DRL 58 375 0 06 Jun 2019
Hamiltonian Neural Networks S. Greydanus Misko Dzamba J. Yosinski PINN AI4CE 65 876 0 04 Jun 2019
COBRA: Data-Efficient Model-Based RL through Unsupervised Object Discovery and Curiosity-Driven Exploration Nicholas Watters Loic Matthey Matko Bosnjak Christopher P. Burgess Alexander Lerchner OffRL 102 117 0 22 May 2019
Emerging Convolutions for Generative Normalizing Flows Emiel Hoogeboom Rianne van den Berg Max Welling DRL 55 98 0 30 Jan 2019
Towards a Definition of Disentangled Representations I. Higgins David Amos David Pfau S. Racanière Loic Matthey Danilo Jimenez Rezende Alexander Lerchner OCL DRL 77 475 0 05 Dec 2018
Learning Latent Dynamics for Planning from Pixels Danijar Hafner Timothy Lillicrap Ian S. Fischer Ruben Villegas David R Ha Honglak Lee James Davidson BDL 73 1,416 0 12 Nov 2018
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models Will Grathwohl Ricky T. Q. Chen J. Bettencourt Ilya Sutskever David Duvenaud DRL 68 861 0 02 Oct 2018
Glow: Generative Flow with Invertible 1x1 Convolutions Diederik P. Kingma Prafulla Dhariwal BDL DRL 214 3,110 0 09 Jul 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 234 5,024 0 19 Jun 2018
Neural Autoregressive Flows Chin-Wei Huang David M. Krueger Alexandre Lacoste Aaron Courville DRL AI4CE 84 439 0 03 Apr 2018
Generalizing Hamiltonian Monte Carlo with Neural Networks Daniel Levy Matthew D. Hoffman Jascha Narain Sohl-Dickstein BDL 51 130 0 25 Nov 2017
Progressive Growing of GANs for Improved Quality, Stability, and Variation Tero Karras Timo Aila S. Laine J. Lehtinen GAN 109 7,318 0 27 Oct 2017
Masked Autoregressive Flow for Density Estimation George Papamakarios Theo Pavlakou Iain Murray 137 1,343 0 19 May 2017
Improving Variational Inference with Inverse Autoregressive Flow Diederik P. Kingma Tim Salimans Rafal Jozefowicz Xi Chen Ilya Sutskever Max Welling BDL DRL 85 1,805 0 15 Jun 2016
Faster Eigenvector Computation via Shift-and-Invert Preconditioning Dan Garber Laurent Dinh Chi Jin Jascha Narain Sohl-Dickstein Samy Bengio Praneeth Netrapalli Aaron Sidford 193 3,681 0 26 May 2016
Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images Manuel Watter Jost Tobias Springenberg Joschka Boedecker Martin Riedmiller BDL 50 839 0 24 Jun 2015
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 258 4,143 0 21 May 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 907 149,474 0 22 Dec 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 372 16,962 0 20 Dec 2013