ML Anthology

Chawla, Nitesh

7 publications

ICLR 2023 Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization Chunhui Zhang, Yijun Tian, Mingxuan Ju, Zheyuan Liu, Yanfang Ye, Nitesh Chawla, Chuxu Zhang
ICLR 2023 Deep Ensembles for Graphs with Higher-Order Dependencies Steven Krieg, William Burgis, Patrick Soga, Nitesh Chawla
ICLR 2023 Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency Yijun Tian, Chuxu Zhang, Zhichun Guo, Xiangliang Zhang, Nitesh Chawla
NeurIPS 2023 What Can Large Language Models Do in Chemistry? a Comprehensive Benchmark on Eight Tasks Taicheng Guo, Kehan Guo, Bozhao Nan, Zhenwen Liang, Zhichun Guo, Nitesh Chawla, Olaf Wiest, Xiangliang Zhang
ICLR 2022 Compositional Training for End-to-End Deep AUC Maximization Zhuoning Yuan, Zhishuai Guo, Nitesh Chawla, Tianbao Yang
LoG 2022 FakeEdge: Alleviate Dataset Shift in Link Prediction Kaiwen Dong, Yijun Tian, Zhichun Guo, Yang Yang, Nitesh Chawla
NeurIPSW 2022 NOSMOG: Learning Noise-Robust and Structure-Aware MLPs on Graphs Yijun Tian, Chuxu Zhang, Zhichun Guo, Xiangliang Zhang, Nitesh Chawla