Yujia Li

According to our database, Yujia Li authored at least 33 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Solving MaxSAT with Matrix Multiplication.

David Warde-Farley, Vinod Nair, Yujia Li, Ivan Lobov, Felix Gimeno, Simon Osindero

CoRR, 2023

2022

Competition-Level Code Generation with AlphaCode.

Yujia Li, David H. Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, Thomas Hubert, Peter Choy, Cyprien de Masson d'Autume, Igor Babuschkin, Xinyun Chen, Po-Sen Huang, Johannes Welbl, Sven Gowal, Alexey Cherepanov, James Molloy, Daniel J. Mankowitz, Esme Sutherland Robson, Pushmeet Kohli, Nando de Freitas, Koray Kavukcuoglu, Oriol Vinyals

CoRR, 2022

2021

Scaling Language Models: Methods, Analysis & Insights from Training Gopher.

Jack W. Rae, Sebastian Borgeaud, Trevor Cai, Katie Millican, Jordan Hoffmann, H. Francis Song, John Aslanides, Sarah Henderson, Roman Ring, Susannah Young, Eliza Rutherford, Tom Hennigan, Jacob Menick, Albin Cassirer, Richard Powell, George van den Driessche, Lisa Anne Hendricks, Maribeth Rauh, Po-Sen Huang, Amelia Glaese, Johannes Welbl, Sumanth Dathathri, Saffron Huang, Jonathan Uesato, John Mellor, Irina Higgins, Antonia Creswell, Nat McAleese, Amy Wu, Erich Elsen, Siddhant M. Jayakumar, Elena Buchatskaya, David Budden, Esme Sutherland, Karen Simonyan, Michela Paganini, Laurent Sifre, Lena Martens, Xiang Lorraine Li, Adhiguna Kuncoro, Aida Nematzadeh, Elena Gribovskaya, Domenic Donato, Angeliki Lazaridou, Arthur Mensch, Jean-Baptiste Lespiau, Maria Tsimpoukelli, Nikolai Grigorev, Doug Fritz, Thibault Sottiaux, Mantas Pajarskas, Toby Pohlen, Zhitao Gong, Daniel Toyama, Cyprien de Masson d'Autume, Yujia Li, Tayfun Terzi, Vladimir Mikulik, Igor Babuschkin, Aidan Clark, Diego de Las Casas, Aurelia Guy, Chris Jones, James Bradbury, Matthew J. Johnson, Blake A. Hechtman, Laura Weidinger, Iason Gabriel, William Isaac, Edward Lockhart, Simon Osindero, Laura Rimell, Chris Dyer, Oriol Vinyals, Kareem Ayoub, Jeff Stanway, Lorrayne Bennett, Demis Hassabis, Koray Kavukcuoglu, Geoffrey Irving

CoRR, 2021

WikiGraphs: A Wikipedia Text - Knowledge Graph Paired Dataset.

Luyu Wang, Yujia Li, Özlem Aslan, Oriol Vinyals

CoRR, 2021

ETA Prediction with Graph Neural Networks in Google Maps.

Austin Derrow-Pinion, Jennifer She, David Wong, Oliver Lange, Todd Hester, Luis Perez, Marc Nunkesser, Seongjae Lee, Xueying Guo, Brett Wiltshire, Peter W. Battaglia, Vishal Gupta, Ang Li, Zhongwen Xu, Alvaro Sanchez-Gonzalez, Yujia Li, Petar Velickovic

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Solving Mixed Integer Programs Using Neural Networks.

Vinod Nair, Sergey Bartunov, Felix Gimeno, Ingrid von Glehn, Pawel Lichocki, Ivan Lobov, Brendan O'Donoghue, Nicolas Sonnerat, Christian Tjandraatmadja, Pengming Wang, Ravichandra Addanki, Tharindi Hapuarachchi, Thomas Keck, James Keeling, Pushmeet Kohli, Ira Ktena, Yujia Li, Oriol Vinyals, Yori Zwols

CoRR, 2020

Strong Generalization and Efficiency in Neural Programs.

Yujia Li, Felix Gimeno, Pushmeet Kohli, Oriol Vinyals

CoRR, 2020

Reinforced Genetic Algorithm Learning for Optimizing Computation Graphs.

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

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

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

Xujie Si, Yujia Li, Vinod Nair, Felix Gimeno

CoRR, 2019

Efficient Graph Generation with Graph Recurrent Attention Networks.

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

CoRR, 2019

REGAL: Transfer Learning For Fast Optimization of Computation Graphs.

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

CoRR, 2019

Efficient Graph Generation with Graph Recurrent Attention Networks.

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

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Graph Matching Networks for Learning the Similarity of Graph Structured Objects.

Yujia Li, Chenjie Gu, Thomas Dullien, Oriol Vinyals, Pushmeet Kohli

Proceedings of the 36th International Conference on Machine Learning, 2019

CompILE: Compositional Imitation Learning and Execution.

Thomas Kipf, Yujia Li, Hanjun Dai, Vinícius Flores Zambaldi, Alvaro Sanchez-Gonzalez, Edward Grefenstette, Pushmeet Kohli, Peter W. Battaglia

Proceedings of the 36th International Conference on Machine Learning, 2019

Deep reinforcement learning with relational inductive biases.

Vinícius Flores Zambaldi, David Raposo, Adam Santoro, Victor Bapst, Yujia Li, Igor Babuschkin, Karl Tuyls, David P. Reichert, Timothy P. Lillicrap, Edward Lockhart, Murray Shanahan, Victoria Langston, Razvan Pascanu, Matthew M. Botvinick, Oriol Vinyals, Peter W. Battaglia

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

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

Thomas Kipf, Yujia Li, Hanjun Dai, Vinícius Flores Zambaldi, Edward Grefenstette, Pushmeet Kohli, Peter W. Battaglia

CoRR, 2018

Relational Deep Reinforcement Learning.

Vinícius Flores Zambaldi, David Raposo, Adam Santoro, Victor Bapst, Yujia Li, Igor Babuschkin, Karl Tuyls, David P. Reichert, Timothy P. Lillicrap, Edward Lockhart, Murray Shanahan, Victoria Langston, Razvan Pascanu, Matthew M. Botvinick, Oriol Vinyals, Peter W. Battaglia

CoRR, 2018

Relational inductive biases, deep learning, and graph networks.

Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinícius Flores Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, Çaglar Gülçehre, H. Francis Song, Andrew J. Ballard, Justin Gilmer, George E. Dahl, Ashish Vaswani, Kelsey R. Allen, Charles Nash, Victoria Langston, Chris Dyer, Nicolas Heess, Daan Wierstra, Pushmeet Kohli, Matthew M. Botvinick, Oriol Vinyals, Yujia Li, Razvan Pascanu

CoRR, 2018

Learning Deep Generative Models of Graphs.

Yujia Li, Oriol Vinyals, Chris Dyer, Razvan Pascanu, Peter W. Battaglia

CoRR, 2018

2017

Building More Expressive Structured Models.

Yujia Li

PhD thesis, 2017

Imagination-Augmented Agents for Deep Reinforcement Learning.

Theophane Weber, Sébastien Racanière, David P. Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adrià Puigdomènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, Razvan Pascanu, Peter W. Battaglia, David Silver, Daan Wierstra

CoRR, 2017

Learning model-based planning from scratch.

Razvan Pascanu, Yujia Li, Oriol Vinyals, Nicolas Heess, Lars Buesing, Sébastien Racanière, David P. Reichert, Theophane Weber, Daan Wierstra, Peter W. Battaglia

CoRR, 2017

Imagination-Augmented Agents for Deep Reinforcement Learning.

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

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Dualing GANs.

Yujia Li, Alexander G. Schwing, Kuan-Chieh Wang, Richard S. Zemel

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

The Variational Fair Autoencoder.

Christos Louizos, Kevin Swersky, Yujia Li, Max Welling, Richard S. Zemel

Proceedings of the 4th International Conference on Learning Representations, 2016

Gated Graph Sequence Neural Networks.

Yujia Li, Daniel Tarlow, Marc Brockschmidt, Richard S. Zemel

Proceedings of the 4th International Conference on Learning Representations, 2016

Understanding the Effective Receptive Field in Deep Convolutional Neural Networks.

Wenjie Luo, Yujia Li, Raquel Urtasun, Richard S. Zemel

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Generative Moment Matching Networks.

Yujia Li, Kevin Swersky, Richard S. Zemel

Proceedings of the 32nd International Conference on Machine Learning, 2015

Feedback-based handwriting recognition from inertial sensor data for wearable devices.

Yujia Li, Kaisheng Yao, Geoffrey Zweig

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

2014

Mean-Field Networks.

Yujia Li, Richard S. Zemel

CoRR, 2014

Learning unbiased features.

Yujia Li, Kevin Swersky, Richard S. Zemel

CoRR, 2014

High Order Regularization for Semi-Supervised Learning of Structured Output Problems.

Yujia Li, Richard S. Zemel

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Exploring Compositional High Order Pattern Potentials for Structured Output Learning.

Yujia Li, Daniel Tarlow, Richard S. Zemel

Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013