Neural Expectation Maximization

11 August 2017

Klaus Greff

Sjoerd van Steenkiste

Jürgen Schmidhuber

OCL

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Papers citing "Neural Expectation Maximization"

23 / 73 papers shown

Title
Slot Contrastive Networks: A Contrastive Approach for Representing Objects Evan Racah Sarath Chandar OCL DRL 21 14 0 18 Jul 2020
Learning Physical Graph Representations from Visual Scenes Daniel M. Bear Chaofei Fan Damian Mrowca Yunzhu Li S. Alter ... Jeremy Schwartz Li Fei-Fei Jiajun Wu J. Tenenbaum Daniel L. K. Yamins SSL GNN SSeg AI4CE 45 79 0 22 Jun 2020
Learning Unsupervised Hierarchical Part Decomposition of 3D Objects from a Single RGB Image Despoina Paschalidou Luc van Gool Andreas Geiger 3DV OCL 34 107 0 02 Apr 2020
SPACE: Unsupervised Object-Oriented Scene Representation via Spatial Attention and Decomposition Zhixuan Lin Yi-Fu Wu Skand Peri Weihao Sun Gautam Singh Fei Deng Jindong Jiang Sungjin Ahn BDL OCL 3DPC 45 246 0 08 Jan 2020
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing V. Monga Yuelong Li Yonina C. Eldar 46 999 0 22 Dec 2019
Exploiting Spatial Invariance for Scalable Unsupervised Object Tracking Eric Crawford Joelle Pineau 50 66 0 20 Nov 2019
IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks Youngwoon Lee E. Hu Zhengyu Yang Alexander Yin Joseph J. Lim 31 121 0 17 Nov 2019
SCALOR: Generative World Models with Scalable Object Representations Jindong Jiang Sepehr Janghorbani Gerard de Melo Sungjin Ahn OCL DRL 37 132 0 06 Oct 2019
LAVAE: Disentangling Location and Appearance Andrea Dittadi Ole Winther OCL BDL DRL 12 6 0 25 Sep 2019
A Perspective on Objects and Systematic Generalization in Model-Based RL Sjoerd van Steenkiste Klaus Greff Jürgen Schmidhuber OCL OffRL 17 31 0 03 Jun 2019
Emergence of Object Segmentation in Perturbed Generative Models Adam Bielski Paolo Favaro 25 99 0 29 May 2019
Object Discovery with a Copy-Pasting GAN Relja Arandjelović Andrew Zisserman 27 57 0 27 May 2019
Unsupervised and interpretable scene discovery with Discrete-Attend-Infer-Repeat Duo Wang M. Jamnik Pietro Lió BDL OCL 26 5 0 14 Mar 2019
Unsupervised Discovery of Parts, Structure, and Dynamics Zhenjia Xu Zhijian Liu Chen Sun Kevin Patrick Murphy William T. Freeman J. Tenenbaum Jiajun Wu OCL 30 61 0 12 Mar 2019
Interpreting and Understanding Graph Convolutional Neural Network using Gradient-based Attribution Method Shangsheng Xie Mingming Lu FAtt GNN 36 16 0 09 Mar 2019
Multi-Object Representation Learning with Iterative Variational Inference Klaus Greff Raphael Lopez Kaufman Rishabh Kabra Nicholas Watters Christopher P. Burgess Daniel Zoran Loic Matthey M. Botvinick Alexander Lerchner OCL SSL 13 499 0 01 Mar 2019
Learning Neural Models for End-to-End Clustering B. Meier Ismail Elezi Mohammadreza Amirian Oliver Durr Thilo Stadelmann SSL 22 16 0 11 Jul 2018
Learning to Decompose and Disentangle Representations for Video Prediction Jun-Ting Hsieh Bingbin Liu De-An Huang Li Fei-Fei Juan Carlos Niebles DRL 138 305 0 11 Jun 2018
Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects Adam R. Kosiorek Hyunjik Kim Ingmar Posner Yee Whye Teh BDL 29 256 0 05 Jun 2018
The Limits and Potentials of Deep Learning for Robotics Niko Sünderhauf Oliver Brock Walter J. Scheirer R. Hadsell Dieter Fox ... B. Upcroft Pieter Abbeel Wolfram Burgard Michael Milford Peter Corke 15 522 0 18 Apr 2018
Relational Neural Expectation Maximization: Unsupervised Discovery of Objects and their Interactions Sjoerd van Steenkiste Michael Chang Klaus Greff Jürgen Schmidhuber BDL OCL DRL 34 290 0 28 Feb 2018
One Big Net For Everything Jürgen Schmidhuber CLL 26 34 0 24 Feb 2018
Recurrent Ladder Networks Isabeau Prémont-Schwarz Alexander Ilin T. Hao Antti Rasmus Rinu Boney Harri Valpola 30 41 0 28 Jul 2017