Exploring Compositional High Order Pattern Potentials for Structured Output Learning. - Yujia Li 001; Daniel Tarlow; Richard S. Zemel (CVPR, 2013)

High Order Regularization for Semi-Supervised Learning of Structured Output Problems. - Yujia Li 001; Richard S. Zemel (ICML, 2014)

Learning unbiased features. - Yujia Li 001; Kevin Swersky; Richard S. Zemel (CoRR, 2014)

Mean-Field Networks. - Yujia Li 001; Richard S. Zemel (CoRR, 2014)

Feedback-based handwriting recognition from inertial sensor data for wearable devices. - Yujia Li 001; Kaisheng Yao; Geoffrey Zweig (ICASSP, 2015)

Generative Moment Matching Networks. - Yujia Li 001; Kevin Swersky; Richard S. Zemel (ICML, 2015)

Understanding the Effective Receptive Field in Deep Convolutional Neural Networks. - Wenjie Luo 002; Yujia Li 001; Raquel Urtasun; Richard S. Zemel (NIPS, 2016)

Gated Graph Sequence Neural Networks. - Yujia Li 001; Daniel Tarlow; Marc Brockschmidt; Richard S. Zemel (ICLR (Poster), 2016)

The Variational Fair Autoencoder. - Christos Louizos; Kevin Swersky; Yujia Li 001; Max Welling; Richard S. Zemel (ICLR, 2016)

Dualing GANs. - Yujia Li 001; Alexander G. Schwing; Kuan-Chieh Wang; Richard S. Zemel (NIPS, 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 001; Razvan Pascanu; Peter W. Battaglia; et al. (NIPS, 2017)

Learning model-based planning from scratch. - Razvan Pascanu; Yujia Li 001; 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. - Theophane Weber; Sébastien Racanière; David P. Reichert; Lars Buesing; Arthur Guez; Danilo Jimenez Rezende; Adrià Puigdomènech Badia; Oriol Vinyals; Nicolas Heess; Yujia Li 001; Razvan Pascanu; Peter W. Battaglia; et al. (CoRR, 2017)

Building More Expressive Structured Models. - Yujia Li 001 (2017)

Learning Deep Generative Models of Graphs. - Yujia Li 001; Oriol Vinyals; Chris Dyer; Razvan Pascanu; 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 001; Çaglar Gülçehre; H. Francis Song; et al. (CoRR, 2018)

Relational Deep Reinforcement Learning. - Vinícius Flores Zambaldi; David Raposo; Adam Santoro; Victor Bapst; Yujia Li 001; Igor Babuschkin; Karl Tuyls; David P. Reichert; Timothy P. Lillicrap; Edward Lockhart; Murray Shanahan; Victoria Langston; et al. (CoRR, 2018)

Compositional Imitation Learning: Explaining and executing one task at a time. - Thomas Kipf; Yujia Li 001; Hanjun Dai; Vinícius Flores Zambaldi; Edward Grefenstette; Pushmeet Kohli; Peter W. Battaglia (CoRR, 2018)

Deep reinforcement learning with relational inductive biases. - Vinícius Flores Zambaldi; David Raposo; Adam Santoro; Victor Bapst; Yujia Li 001; Igor Babuschkin; Karl Tuyls; David P. Reichert; Timothy P. Lillicrap; Edward Lockhart; Murray Shanahan; Victoria Langston; et al. (ICLR (Poster), 2019)

CompILE: Compositional Imitation Learning and Execution. - Thomas Kipf; Yujia Li 001; Hanjun Dai; Vinícius Flores Zambaldi; Alvaro Sanchez-Gonzalez; Edward Grefenstette; Pushmeet Kohli; Peter W. Battaglia (ICML, 2019)

Graph Matching Networks for Learning the Similarity of Graph Structured Objects. - Yujia Li 001; Chenjie Gu; Thomas Dullien; Oriol Vinyals; Pushmeet Kohli (ICML, 2019)

Learning Transferable Graph Exploration. - Hanjun Dai; Yujia Li 001; Chenglong Wang; Rishabh Singh; Po-Sen Huang; Pushmeet Kohli (NeurIPS, 2019)

Efficient Graph Generation with Graph Recurrent Attention Networks. - Renjie Liao; Yujia Li 001; Yang Song 011; Shenlong Wang; William L. Hamilton; David Duvenaud; Raquel Urtasun; Richard S. Zemel (NeurIPS, 2019)

REGAL: Transfer Learning For Fast Optimization of Computation Graphs. - Aditya Paliwal; Felix Gimeno; Vinod Nair; Yujia Li 001; Miles Lubin; Pushmeet Kohli; Oriol Vinyals (CoRR, 2019)

Efficient Graph Generation with Graph Recurrent Attention Networks. - Renjie Liao; Yujia Li 001; Yang Song 011; Shenlong Wang; Charlie Nash; William L. Hamilton; David Duvenaud; Raquel Urtasun; Richard S. Zemel (CoRR, 2019)

Prioritized Unit Propagation with Periodic Resetting is (Almost) All You Need for Random SAT Solving. - Xujie Si; Yujia Li 001; Vinod Nair; Felix Gimeno (CoRR, 2019)

Reinforced Genetic Algorithm Learning for Optimizing Computation Graphs. - Aditya Paliwal; Felix Gimeno; Vinod Nair; Yujia Li 001; Miles Lubin; Pushmeet Kohli; Oriol Vinyals (ICLR, 2020)

Strong Generalization and Efficiency in Neural Programs. - Yujia Li 001; Felix Gimeno; Pushmeet Kohli; Oriol Vinyals (CoRR, 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 001; Ravichandra Addanki; Tharindi Hapuarachchi; et al. (CoRR, 2020)

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; et al. (CIKM, 2021)

WikiGraphs: A Wikipedia Text - Knowledge Graph Paired Dataset. - Luyu Wang; Yujia Li 001; Özlem Aslan; Oriol Vinyals (CoRR, 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; et al. (CoRR, 2021)

Competition-Level Code Generation with AlphaCode. - Yujia Li 001; David H. Choi; Junyoung Chung; Nate Kushman; Julian Schrittwieser; Rémi Leblond; Tom Eccles; James Keeling; Felix Gimeno; Agustin Dal Lago; Thomas Hubert; Peter Choy; et al. (CoRR, 2022)

Transformers Meet Directed Graphs. - Simon Geisler; Yujia Li 001; Daniel J. Mankowitz; Ali Taylan Cemgil; Stephan Günnemann; Cosmin Paduraru (ICML, 2023)

Solving MaxSAT with Matrix Multiplication. - David Warde-Farley; Vinod Nair; Yujia Li 001; Ivan Lobov; Felix Gimeno; Simon Osindero (CoRR, 2023)

Faster sorting algorithms discovered using deep reinforcement learning. - Daniel J. Mankowitz; Andrea Michi; Anton Zhernov; Marco Gelmi; Marco Selvi; Cosmin Paduraru; Edouard Leurent; Shariq Iqbal; Jean-Baptiste Lespiau; Alex Ahern; Thomas Köppe; Kevin Millikin; et al. (Nat., 2023)