Size-Invariant Graph Representations for Graph Classification Extrapolations. - Beatrice Bevilacqua; Yangze Zhou; Bruno Ribeiro 001 (ICML, 2021)

Set Twister for Single-hop Node Classification. - Yangze Zhou; Vinayak A. Rao; Bruno Ribeiro 001 (CoRR, 2021)

OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs. - Yangze Zhou; Gitta Kutyniok; Bruno Ribeiro 001 (NeurIPS, 2022)

Bias Challenges in Counterfactual Data Augmentation. - S. Chandra Mouli; Yangze Zhou; Bruno Ribeiro 001 (CoRR, 2022)

Double Permutation Equivariance for Knowledge Graph Completion. - Jianfei Gao 001; Yangze Zhou; Bruno Ribeiro 001 (CoRR, 2023)

Uplift Modeling based on Graph Neural Network Combined with Causal Knowledge. - Haowen Wang; Xinyan Ye; Yangze Zhou; Zhiyi Zhang; Longhan Zhang; Jing Jiang (CoRR, 2023)

Improving Load Forecasting Performance via Sample Reweighting. - Chenxi Wang; Yangze Zhou; Qingsong Wen; Yi Wang 022 (IEEE Trans. Smart Grid, 2023)

Update Scheduling for ADMM-Based Energy Sharing in Virtual Power Plants Considering Massive Prosumer Access. - Cheng Feng; Kedi Zheng; Yangze Zhou; Peter Palensky; Qixin Chen (IEEE Trans. Smart Grid, 2023)

Load Data Valuation in Multi-Energy Systems: An End-to-End Approach. - Yangze Zhou; Qingsong Wen; Jie Song 002; Xueyuan Cui; Yi Wang 022 (IEEE Trans. Smart Grid, 2024)

Interpretable Load Forecasting via Representation Learning of Geo-distributed Meteorological Factors. - Yangze Zhou; Guoxin Lin; Gonghao Zhang; Yi Wang (CoRR, 2025)