A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised
Learning

A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning

16 October 2017

Papers citing "A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning"

14 / 64 papers shown

Title
Deep Factors for Forecasting Bernie Wang Alex Smola Danielle C. Maddix Jan Gasthaus Dean Phillips Foster Tim Januschowski BDL 21 170 0 28 May 2019
Physics-as-Inverse-Graphics: Unsupervised Physical Parameter Estimation from Video Miguel Jaques Michael G. Burke Timothy M. Hospedales VGen PINN 21 45 0 27 May 2019
Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces P. Becker Harit Pandya Gregor H. W. Gebhardt Cheng Zhao James Taylor Gerhard Neumann BDL 13 94 0 17 May 2019
Disentangling Factors of Variation Using Few Labels Francesco Locatello Michael Tschannen Stefan Bauer Gunnar Rätsch Bernhard Schölkopf Olivier Bachem DRL CML CoGe 34 123 0 03 May 2019
Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control Jeremy Morton F. Witherden Mykel J Kochenderfer 21 45 0 26 Feb 2019
Deep Factors with Gaussian Processes for Forecasting Danielle C. Maddix Bernie Wang Alex Smola BDL UQCV AI4TS 27 41 0 30 Nov 2018
A General Method for Amortizing Variational Filtering Joseph Marino Milan Cvitkovic Yisong Yue 27 34 0 13 Nov 2018
Deep Dynamical Modeling and Control of Unsteady Fluid Flows Jeremy Morton F. Witherden A. Jameson Mykel J. Kochenderfer AI4CE 19 161 0 18 May 2018
Generative Temporal Models with Spatial Memory for Partially Observed Environments Marco Fraccaro Danilo Jimenez Rezende Yori Zwols Alexander Pritzel S. M. Ali Eslami Fabio Viola 31 28 0 25 Apr 2018
Disentangling Controllable and Uncontrollable Factors of Variation by Interacting with the World Yoshihide Sawada DRL 21 10 0 19 Apr 2018
Variational Encoding of Complex Dynamics Carlos X. Hernández H. Wayment-Steele Mohammad M. Sultan B. Husic Vijay S. Pande AI4CE 25 138 0 23 Nov 2017
A Compositional Object-Based Approach to Learning Physical Dynamics Michael Chang T. Ullman Antonio Torralba J. Tenenbaum AI4CE OCL 241 439 0 01 Dec 2016
Interaction Networks for Learning about Objects, Relations and Physics Peter W. Battaglia Razvan Pascanu Matthew Lai Danilo Jimenez Rezende Koray Kavukcuoglu AI4CE OCL PINN GNN 283 1,401 0 01 Dec 2016
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network Wenzhe Shi Jose Caballero Ferenc Huszár J. Totz Andrew P. Aitken Rob Bishop Daniel Rueckert Zehan Wang SupR 231 5,180 0 16 Sep 2016