103 citations · 126 across the 17 of their papers we have counts for
5 papers · 1 filter
Improving Out-of-Distribution Robustness of Classifiers via Generative Interpolation
Haoyue Bai, Ceyuan Yang, Yinghao Xu +2
Deep neural networks achieve superior performance for learning from independent and identically distributed (i.i.d.) data. However, their performance deteriorates significantly whe…
A Lightweight and Accurate Spatial-Temporal Transformer for Traffic Forecasting
Guanyao Li, Shuhan Zhong, S. -H. Gary Chan +3
We study the forecasting problem for traffic with dynamic, possibly periodical, and joint spatial-temporal dependency between regions. Given the aggregated inflow and outflow traff…
NAS-OoD: Neural Architecture Search for Out-of-Distribution Generalization
Haoyue Bai, Fengwei Zhou, Lanqing Hong +3
Recent advances on Out-of-Distribution (OoD) generalization reveal the robustness of deep learning models against distribution shifts. However, existing works focus on OoD algorith…
DecAug: Out-of-Distribution Generalization via Decomposed Feature Representation and Semantic Augmentation
Haoyue Bai, Rui Sun, Lanqing Hong +5
While deep learning demonstrates its strong ability to handle independent and identically distributed (IID) data, it often suffers from out-of-distribution (OoD) generalization, wh…
Representation Learning of Pedestrian Trajectories Using Actor-Critic Sequence-to-Sequence Autoencoder
Ka-Ho Chow, Anish Hiranandani, Yifeng Zhang +1
Representation learning of pedestrian trajectories transforms variable-length timestamp-coordinate tuples of a trajectory into a fixed-length vector representation that summarizes…