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Automatically Composing Representation Transformations as a Means for Generalization

12 July 2018

Abhishek Gupta

Papers citing "Automatically Composing Representation Transformations as a Means for Generalization"

36 / 36 papers shown

Title
Breaking Neural Network Scaling Laws with Modularity Akhilan Boopathy Sunshine Jiang William Yue Jaedong Hwang Abhiram Iyer Ila Fiete OOD 115 2 0 09 Sep 2024
A Study of Compositional Generalization in Neural Models Tim Klinger D. Adjodah Vincent Marois Joshua Joseph Matthew D Riemer Alex Pentland Murray Campbell CoGe NAI 181 13 0 16 Jun 2020
Towards a Definition of Disentangled Representations I. Higgins David Amos David Pfau S. Racanière Loic Matthey Danilo Jimenez Rezende Alexander Lerchner OCL DRL 108 480 0 05 Dec 2018
Learning to Reason with Third-Order Tensor Products Imanol Schlag Jürgen Schmidhuber NAI 56 64 0 29 Nov 2018
Modular Networks: Learning to Decompose Neural Computation Louis Kirsch Julius Kunze David Barber 72 111 0 13 Nov 2018
Modular meta-learning Ferran Alet Tomás Lozano-Pérez L. Kaelbling OffRL 78 122 0 26 Jun 2018
Unsupervised Meta-Learning for Reinforcement Learning Abhishek Gupta Benjamin Eysenbach Chelsea Finn Sergey Levine SSL OffRL 91 107 0 12 Jun 2018
Relational inductive biases, deep learning, and graph networks Peter W. Battaglia Jessica B. Hamrick V. Bapst Alvaro Sanchez-Gonzalez V. Zambaldi ... Pushmeet Kohli M. Botvinick Oriol Vinyals Yujia Li Razvan Pascanu AI4CE NAI 769 3,129 0 04 Jun 2018
Graph networks as learnable physics engines for inference and control Alvaro Sanchez-Gonzalez N. Heess Jost Tobias Springenberg J. Merel Martin Riedmiller R. Hadsell Peter W. Battaglia GNN AI4CE PINN OCL 218 602 0 04 Jun 2018
HOUDINI: Lifelong Learning as Program Synthesis Lazar Valkov Dipak Chaudhari Akash Srivastava Charles Sutton Swarat Chaudhuri 77 82 0 31 Mar 2018
On First-Order Meta-Learning Algorithms Alex Nichol Joshua Achiam John Schulman 235 2,237 0 08 Mar 2018
Relational Neural Expectation Maximization: Unsupervised Discovery of Objects and their Interactions Sjoerd van Steenkiste Michael Chang Klaus Greff Jürgen Schmidhuber BDL OCL DRL 209 291 0 28 Feb 2018
Meta-Reinforcement Learning of Structured Exploration Strategies Abhishek Gupta Russell Mendonca YuXuan Liu Pieter Abbeel Sergey Levine OffRL 110 349 0 20 Feb 2018
Recasting Gradient-Based Meta-Learning as Hierarchical Bayes Erin Grant Chelsea Finn Sergey Levine Trevor Darrell Thomas Griffiths BDL 90 510 0 26 Jan 2018
Routing Networks: Adaptive Selection of Non-linear Functions for Multi-Task Learning Clemens Rosenbaum Tim Klinger Matthew D Riemer 84 247 0 03 Nov 2017
A simple neural network module for relational reasoning Adam Santoro David Raposo David Barrett Mateusz Malinowski Razvan Pascanu Peter W. Battaglia Timothy Lillicrap GNN NAI 189 1,615 0 05 Jun 2017
FeUdal Networks for Hierarchical Reinforcement Learning A. Vezhnevets Simon Osindero Tom Schaul N. Heess Max Jaderberg David Silver Koray Kavukcuoglu FedML 96 907 0 03 Mar 2017
PathNet: Evolution Channels Gradient Descent in Super Neural Networks Chrisantha Fernando Dylan Banarse Charles Blundell Yori Zwols David R Ha Andrei A. Rusu Alexander Pritzel Daan Wierstra 75 881 0 30 Jan 2017
Inverse Compositional Spatial Transformer Networks Chen-Hsuan Lin Simon Lucey 72 162 0 12 Dec 2016
A Compositional Object-Based Approach to Learning Physical Dynamics Michael Chang T. Ullman Antonio Torralba J. Tenenbaum AI4CE OCL 386 441 0 01 Dec 2016
Learning Modular Neural Network Policies for Multi-Task and Multi-Robot Transfer Coline Devin Abhishek Gupta Trevor Darrell Pieter Abbeel Sergey Levine OffRL 84 400 0 22 Sep 2016
Learning to learn by gradient descent by gradient descent Marcin Andrychowicz Misha Denil Sergio Gomez Colmenarejo Matthew W. Hoffman David Pfau Tom Schaul Brendan Shillingford Nando de Freitas 124 2,008 0 14 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 159 4,238 0 12 Jun 2016
Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation Tejas D. Kulkarni Karthik Narasimhan A. Saeedi J. Tenenbaum 74 1,137 0 20 Apr 2016
Adaptive Computation Time for Recurrent Neural Networks Alex Graves 117 549 0 29 Mar 2016
Neural Module Networks Jacob Andreas Marcus Rohrbach Trevor Darrell Dan Klein CoGe 139 1,076 0 09 Nov 2015
Spatial Transformer Networks Max Jaderberg Karen Simonyan Andrew Zisserman Koray Kavukcuoglu 314 7,392 0 05 Jun 2015
Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets Armand Joulin Tomas Mikolov TPM 142 412 0 03 Mar 2015
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention Ke Xu Jimmy Ba Ryan Kiros Kyunghyun Cho Aaron Courville Ruslan Salakhutdinov R. Zemel Yoshua Bengio DiffM 350 10,079 0 10 Feb 2015
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 251 4,681 0 21 Dec 2014
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling Junyoung Chung Çağlar Gülçehre Kyunghyun Cho Yoshua Bengio 601 12,741 0 11 Dec 2014
Neural Turing Machines Alex Graves Greg Wayne Ivo Danihelka 108 2,331 0 20 Oct 2014
Learning to Execute Wojciech Zaremba Ilya Sutskever ODL 90 560 0 17 Oct 2014
Recurrent Models of Visual Attention Volodymyr Mnih N. Heess Alex Graves Koray Kavukcuoglu VLM 161 3,656 0 24 Jun 2014
Self-Delimiting Neural Networks Jürgen Schmidhuber 103 37 0 29 Sep 2012
Representation Learning: A Review and New Perspectives Yoshua Bengio Aaron Courville Pascal Vincent OOD SSL 278 12,458 0 24 Jun 2012