259 citations · 510 across the 22 of their papers we have counts for
4 papers · 1 filter
Multimodal Molecular Pretraining via Modality Blending
Qiying Yu, Yudi Zhang, Yuyan Ni +4
Self-supervised learning has recently gained growing interest in molecular modeling for scientific tasks such as AI-assisted drug discovery. Current studies consider leveraging bot…
Spectral Heterogeneous Graph Convolutions via Positive Noncommutative Polynomials
Mingguo He, Zhewei Wei, Shikun Feng +4
Heterogeneous Graph Neural Networks (HGNNs) have gained significant popularity in various heterogeneous graph learning tasks. However, most existing HGNNs rely on spatial domain-ba…
DuETA: Traffic Congestion Propagation Pattern Modeling via Efficient Graph Learning for ETA Prediction at Baidu Maps
Jizhou Huang, Zhengjie Huang, Xiaomin Fang +5
Estimated time of arrival (ETA) prediction, also known as travel time estimation, is a fundamental task for a wide range of intelligent transportation applications, such as navigat…
Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation
Sahil Singla, Eric Wallace, Shi Feng +1
Current methods to interpret deep learning models by generating saliency maps generally rely on two key assumptions. First, they use first-order approximations of the loss function…