47 citations · 102 across the 15 of their papers we have counts for
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cs.LG2023★ 25 cited
MixupExplainer: Generalizing Explanations for Graph Neural Networks with Data Augmentation
Jiaxing Zhang, Dongsheng Luo, Hua Wei
Graph Neural Networks (GNNs) have received increasing attention due to their ability to learn from graph-structured data. However, their predictions are often not interpretable. Po…
cs.LG2023
RegExplainer: Generating Explanations for Graph Neural Networks in Regression Tasks
Jiaxing Zhang, Zhuomin Chen, Hao Mei +3
Graph regression is a fundamental task that has gained significant attention in various graph learning tasks. However, the inference process is often not easily interpretable. Curr…
cs.LG2020★ 2 cited
Accelerating Reinforcement Learning with a Directional-Gaussian-Smoothing Evolution Strategy
Jiaxing Zhang, Hoang Tran, Guannan Zhang
Evolution strategy (ES) has been shown great promise in many challenging reinforcement learning (RL) tasks, rivaling other state-of-the-art deep RL methods. Yet, there are two limi…