Slot Contrastive Networks: A Contrastive Approach for Representing Objects

18 July 2020

Papers citing "Slot Contrastive Networks: A Contrastive Approach for Representing Objects"

6 / 6 papers shown

Title
Learning to Simulate Complex Physics with Graph Networks Alvaro Sanchez-Gonzalez Jonathan Godwin Tobias Pfaff Rex Ying J. Leskovec Peter W. Battaglia PINN AI4CE 123 1,065 0 21 Feb 2020
Exploiting Spatial Invariance for Scalable Unsupervised Object Tracking Eric Crawford Joelle Pineau 98 66 0 20 Nov 2019
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 42 195 0 19 Jun 2019
Learning Representations by Maximizing Mutual Information Across Views Philip Bachman R. Devon Hjelm William Buchwalter SSL 179 1,463 0 03 Jun 2019
Relational Neural Expectation Maximization: Unsupervised Discovery of Objects and their Interactions Sjoerd van Steenkiste Michael Chang Klaus Greff Jürgen Schmidhuber BDL OCL DRL 154 290 0 28 Feb 2018
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 492 1,405 0 01 Dec 2016