Understanding Visual Concepts with Continuation Learning

Understanding Visual Concepts with Continuation Learning

22 February 2016

William F. Whitney

Tejas D. Kulkarni

Papers citing "Understanding Visual Concepts with Continuation Learning"

16 / 16 papers shown

Title
Symmetry-Based Representations for Artificial and Biological General Intelligence I. Higgins S. Racanière Danilo Jimenez Rezende AI4CE 31 44 0 17 Mar 2022
Weakly-Supervised Disentanglement Without Compromises Francesco Locatello Ben Poole Gunnar Rätsch Bernhard Schölkopf Olivier Bachem Michael Tschannen CoGe OOD DRL 184 313 0 07 Feb 2020
Unsupervised Learning of Object Keypoints for Perception and Control Tejas D. Kulkarni Ankush Gupta Catalin Ionescu Sebastian Borgeaud Malcolm Reynolds Andrew Zisserman Volodymyr Mnih SSL OCL 11 193 0 19 Jun 2019
Disentangling Factors of Variation Using Few Labels Francesco Locatello Michael Tschannen Stefan Bauer Gunnar Rätsch Bernhard Schölkopf Olivier Bachem DRL CML CoGe 23 122 0 03 May 2019
Relevance Factor VAE: Learning and Identifying Disentangled Factors Minyoung Kim Yuting Wang Pritish Sahu Vladimir Pavlovic CoGe CML DRL 19 38 0 05 Feb 2019
Automatically Composing Representation Transformations as a Means for Generalization Michael Chang Abhishek Gupta Sergey Levine Thomas L. Griffiths 26 68 0 12 Jul 2018
Flexible Neural Representation for Physics Prediction Damian Mrowca Chengxu Zhuang E. Wang Nick Haber Li Fei-Fei J. Tenenbaum Daniel L. K. Yamins OCL AI4CE 22 248 0 21 Jun 2018
Unsupervised Learning of Object Landmarks through Conditional Image Generation Tomas Jakab Ankush Gupta Hakan Bilen Andrea Vedaldi SSL 33 252 0 20 Jun 2018
Understanding disentangling in $β$ -VAE Christopher P. Burgess I. Higgins Arka Pal Loic Matthey Nicholas Watters Guillaume Desjardins Alexander Lerchner CoGe DRL 11 822 0 10 Apr 2018
Learning Disentangled Joint Continuous and Discrete Representations Emilien Dupont DRL 28 241 0 31 Mar 2018
DARLA: Improving Zero-Shot Transfer in Reinforcement Learning I. Higgins Arka Pal Andrei A. Rusu Loic Matthey Christopher P. Burgess Alexander Pritzel M. Botvinick Charles Blundell Alexander Lerchner DRL 34 409 0 26 Jul 2017
A Compositional Object-Based Approach to Learning Physical Dynamics Michael Chang T. Ullman Antonio Torralba J. Tenenbaum AI4CE OCL 241 438 0 01 Dec 2016
Early Visual Concept Learning with Unsupervised Deep Learning I. Higgins Loic Matthey Xavier Glorot Arka Pal Benigno Uria Charles Blundell S. Mohamed Alexander Lerchner CoGe OCL DRL 18 173 0 17 Jun 2016
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets Xi Chen Yan Duan Rein Houthooft John Schulman Ilya Sutskever Pieter Abbeel GAN 64 4,210 0 12 Jun 2016
Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning William Lotter Gabriel Kreiman David D. Cox SSL 37 927 0 25 May 2016
Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation Tejas D. Kulkarni Karthik Narasimhan A. Saeedi J. Tenenbaum 16 1,125 0 20 Apr 2016