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Scalable Deep Generative Modeling for Sparse Graphs

Jun 28, 2020
Hanjun Dai, Azade Nazi, Yujia Li, Bo Dai, Dale Schuurmans

* ICML 2020 

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A sparse negative binomial mixture model for clustering RNA-seq count data

Dec 05, 2019
Tanbin Rahman, Yujia Li, Tianzhou Ma, Lu Tang, George Tseng


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Prioritized Unit Propagation with Periodic Resetting is (Almost) All You Need for Random SAT Solving

Dec 04, 2019
Xujie Si, Yujia Li, Vinod Nair, Felix Gimeno


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Learning Transferable Graph Exploration

Oct 28, 2019
Hanjun Dai, Yujia Li, Chenglong Wang, Rishabh Singh, Po-Sen Huang, Pushmeet Kohli

* To appear in NeurIPS 2019 

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Efficient Graph Generation with Graph Recurrent Attention Networks

Oct 02, 2019
Renjie Liao, Yujia Li, Yang Song, Shenlong Wang, Charlie Nash, William L. Hamilton, David Duvenaud, Raquel Urtasun, Richard S. Zemel

* Neural Information Processing Systems (NeurIPS) 2019 

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Graph Convolutional Transformer: Learning the Graphical Structure of Electronic Health Records

Jun 28, 2019
Edward Choi, Zhen Xu, Yujia Li, Michael W. Dusenberry, Gerardo Flores, Yuan Xue, Andrew M. Dai


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Fast Training of Sparse Graph Neural Networks on Dense Hardware

Jun 27, 2019
Matej Balog, Bart van Merriënboer, Subhodeep Moitra, Yujia Li, Daniel Tarlow


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REGAL: Transfer Learning For Fast Optimization of Computation Graphs

May 30, 2019
Aditya Paliwal, Felix Gimeno, Vinod Nair, Yujia Li, Miles Lubin, Pushmeet Kohli, Oriol Vinyals


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Graph Matching Networks for Learning the Similarity of Graph Structured Objects

May 12, 2019
Yujia Li, Chenjie Gu, Thomas Dullien, Oriol Vinyals, Pushmeet Kohli

* Accepted as a conference paper at ICML 2019 

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Compositional Imitation Learning: Explaining and executing one task at a time

Dec 04, 2018
Thomas Kipf, Yujia Li, Hanjun Dai, Vinicius Zambaldi, Edward Grefenstette, Pushmeet Kohli, Peter Battaglia

* Presented at the Learning by Instruction (LBI) Workshop at NeurIPS 2018 

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Relational inductive biases, deep learning, and graph networks

Oct 17, 2018
Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinicius Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, Caglar Gulcehre, Francis Song, Andrew Ballard, Justin Gilmer, George Dahl, Ashish Vaswani, Kelsey Allen, Charles Nash, Victoria Langston, Chris Dyer, Nicolas Heess, Daan Wierstra, Pushmeet Kohli, Matt Botvinick, Oriol Vinyals, Yujia Li, Razvan Pascanu


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Proximal Policy Optimization and its Dynamic Version for Sequence Generation

Aug 24, 2018
Yi-Lin Tuan, Jinzhi Zhang, Yujia Li, Hung-yi Lee


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Relational Deep Reinforcement Learning

Jun 28, 2018
Vinicius Zambaldi, David Raposo, Adam Santoro, Victor Bapst, Yujia Li, Igor Babuschkin, Karl Tuyls, David Reichert, Timothy Lillicrap, Edward Lockhart, Murray Shanahan, Victoria Langston, Razvan Pascanu, Matthew Botvinick, Oriol Vinyals, Peter Battaglia


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Learning Deep Generative Models of Graphs

Mar 08, 2018
Yujia Li, Oriol Vinyals, Chris Dyer, Razvan Pascanu, Peter Battaglia

* 21 pages 

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Imagination-Augmented Agents for Deep Reinforcement Learning

Feb 14, 2018
Théophane Weber, Sébastien Racanière, David P. Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adria Puigdomènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, Razvan Pascanu, Peter Battaglia, Demis Hassabis, David Silver, Daan Wierstra


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Gated Graph Sequence Neural Networks

Sep 22, 2017
Yujia Li, Daniel Tarlow, Marc Brockschmidt, Richard Zemel

* Published as a conference paper in ICLR 2016. Fixed a typo 

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The Variational Fair Autoencoder

Aug 10, 2017
Christos Louizos, Kevin Swersky, Yujia Li, Max Welling, Richard Zemel

* Fixed typo in eq. 3 and 4 

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Learning model-based planning from scratch

Jul 19, 2017
Razvan Pascanu, Yujia Li, Oriol Vinyals, Nicolas Heess, Lars Buesing, Sebastien Racanière, David Reichert, Théophane Weber, Daan Wierstra, Peter Battaglia


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Dualing GANs

Jun 19, 2017
Yujia Li, Alexander Schwing, Kuan-Chieh Wang, Richard Zemel


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Understanding the Effective Receptive Field in Deep Convolutional Neural Networks

Jan 25, 2017
Wenjie Luo, Yujia Li, Raquel Urtasun, Richard Zemel


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Generative Moment Matching Networks

Feb 10, 2015
Yujia Li, Kevin Swersky, Richard Zemel


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Learning unbiased features

Dec 17, 2014
Yujia Li, Kevin Swersky, Richard Zemel

* Published in NIPS 2014 Workshop on Transfer and Multitask Learning, see http://nips.cc/Conferences/2014/Program/event.php?ID=4282 

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Mean-Field Networks

Oct 21, 2014
Yujia Li, Richard Zemel

* Published in ICML 2014 workshop on Learning Tractable Probabilistic Models 

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