Object-Oriented Dynamics Learning through Multi-Level Abstraction

16 April 2019

Papers citing "Object-Oriented Dynamics Learning through Multi-Level Abstraction"

8 / 8 papers shown

Title
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 264 3,101 0 04 Jun 2018
Relational Neural Expectation Maximization: Unsupervised Discovery of Objects and their Interactions Sjoerd van Steenkiste Michael Chang Klaus Greff Jürgen Schmidhuber BDL OCL DRL 82 290 0 28 Feb 2018
Curiosity-driven Exploration by Self-supervised Prediction Deepak Pathak Pulkit Agrawal Alexei A. Efros Trevor Darrell LRM SSL 89 2,416 0 15 May 2017
SfM-Net: Learning of Structure and Motion from Video Sudheendra Vijayanarasimhan Susanna Ricco Cordelia Schmid Rahul Sukthankar Katerina Fragkiadaki MDE 56 440 0 25 Apr 2017
A Compositional Object-Based Approach to Learning Physical Dynamics Michael Chang T. Ullman Antonio Torralba J. Tenenbaum AI4CE OCL 294 439 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 403 1,405 0 01 Dec 2016
Fully Convolutional Instance-aware Semantic Segmentation Yi Li Haozhi Qi Jifeng Dai Xiangyang Ji Yichen Wei ISeg SSeg 61 1,004 0 23 Nov 2016
Spatial Transformer Networks Max Jaderberg Karen Simonyan Andrew Zisserman Koray Kavukcuoglu 240 7,361 0 05 Jun 2015