I am a PhD student in computer science at MILA and University of Montreal, advised by Prof. Liam Paull and Prof. Yoshua Bengio. I received my M.S. and B.S. degrees at Georgia Institute of Technology, where I studied computer science with a minor in economics.
My research interests broadly lie in deep learning, computer vision and robotics. Specifically, I am interested in how deep models learn representations to enable 1) better physics and visual reasoning in a modular way and 2) fast and generalizable robot planning in complex environments.
Orthogonal Over-parametrized Training
Weiyang Liu, Rongmei Lin, Zhen Liu, James M Rehg, Liam Paull, Li Xiong, Adrian Weller, Le Song.
Conference on Computer Vision and Pattern Recognition (CVPR), 2021 (Oral)
Exponential Family Estimation via Adversarial Dynamics Embedding
Bo Dai*, Zhen Liu*, Hanjun Dai*, Niao He, Arthur Gretton, Le Song, Dale Schuurmans.
Neural Information Processing Systems (NeurIPS) 2019
Learning towards Minimum Hyperspherical Energy
Weiyang Liu*, Rongmei Lin*, Zhen Liu*, Lixin Liu*, Zhiding Yu, Bo Dai, Le Song.
Neural Information Processing Systems (NeurIPS), 2018
Weiyang Liu*, Zhen Liu*, Zhiding Yu, Bo Dai, Rongmei Lin, Yisen Wang, James Rehg, Le Song.
Conference on Computer Vision and Pattern Recognition (CVPR), 2018 (spotlight)
SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation
Bo Dai, Albert Shaw, Lihong Li, Lin Xiao, Niao He, Zhen Liu, Jianshu Chen, Le Song.
International Conference on Machine Learning (ICML), 2018
One Shot Learning for Semantic Segmentation
Amirreza Shaban, Shray Bansal, Zhen Liu, Irfan Essa, Byron Boots.
The British Machine Vision Conference (BMVC), 2017