Yujia Li
Yujia Li
Research Scientist, DeepMind
Verified email at cs.toronto.edu
TitleCited byYear
Gated graph sequence neural networks
Y Li, D Tarlow, M Brockschmidt, R Zemel
arXiv preprint arXiv:1511.05493, 2015
6472015
Generative moment matching networks
Y Li, K Swersky, R Zemel
International Conference on Machine Learning, 1718-1727, 2015
3642015
Relational inductive biases, deep learning, and graph networks
PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ...
arXiv preprint arXiv:1806.01261, 2018
3402018
Understanding the Effective Receptive Field in Deep Convolutional Neural Networks
W Luo, Y Li, R Urtasun, R Zemel
Advances in Neural Information Processing Systems (NIPS), 2016
2882016
Imagination-Augmented Agents for Deep Reinforcement Learning
T Weber, S Racanière, DP Reichert, L Buesing, A Guez, DJ Rezende, ...
arXiv:1707.06203, 2017
199*2017
The variational fair autoencoder
C Louizos, K Swersky, Y Li, M Welling, R Zemel
arXiv preprint arXiv:1511.00830, 2015
1612015
Learning deep generative models of graphs
Y Li, O Vinyals, C Dyer, R Pascanu, P Battaglia
arXiv preprint arXiv:1803.03324, 2018
1072018
Relational deep reinforcement learning
V Zambaldi, D Raposo, A Santoro, V Bapst, Y Li, I Babuschkin, K Tuyls, ...
arXiv preprint arXiv:1806.01830, 2018
462018
Learning Model-Based Planning from Scratch
R Pascanu, Y Li, O Vinyals, N Heess, L Buesing, S Racanière, D Reichert, ...
arXiv:1707.06170, 2017
442017
Exploring compositional high order pattern potentials for structured output learning
Y Li, D Tarlow, R Zemel
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013
422013
High Order Regularization for Semi-Supervised Learning of Structured Output Problems
Y Li, R Zemel
International Conference on Machine Learning (ICML), 2014
232014
Mean Field Networks
Y Li, R Zemel
ICML workshop on Learning Tractable Probabilistic Models, 2014
212014
Celebrity recommendation with collaborative social topic regression
X Ding, X Jin, Y Li, L Li
Twenty-Third International Joint Conference on Artificial Intelligence, 2013
192013
Deep reinforcement learning with relational inductive biases
V Zambaldi, D Raposo, A Santoro, V Bapst, Y Li, I Babuschkin, K Tuyls, ...
132018
Learning unbiased features
Y Li, K Swersky, R Zemel
NIPS workshop on Transfer and Multi-Task Learnnig, 2014
132014
Dualing GANs
Y Li, A Schwing, KC Wang, R Zemel
Advances in Neural Information Processing Systems, 5606-5616, 2017
92017
Natural motion-based control via wearable and mobile devices
J Wang, Y Li, X Huang, L Wu, W Xiong, K Yao, G Zweig
US Patent App. 14/502,549, 2016
82016
Graph Matching Networks for Learning the Similarity of Graph Structured Objects
Y Li, C Gu, T Dullien, O Vinyals, P Kohli
arXiv preprint arXiv:1904.12787, 2019
62019
REGAL: Transfer Learning For Fast Optimization of Computation Graphs
A Paliwal, F Gimeno, V Nair, Y Li, M Lubin, P Kohli, O Vinyals
arXiv preprint arXiv:1905.02494, 2019
42019
Compositional Imitation Learning: Explaining and executing one task at a time
T Kipf, Y Li, H Dai, V Zambaldi, E Grefenstette, P Kohli, P Battaglia
arXiv preprint arXiv:1812.01483, 2018
32018
The system can't perform the operation now. Try again later.
Articles 1–20