Learning large-scale fuzzy cognitive maps using an evolutionary many-task algorithm. - Chao Wang 099; Jing Liu 006; Kai Wu 003; Chaolong Ying (Appl. Soft Comput., 2021)

Molecular Conformation Generation via Shifting Scores. - Zihan Zhou 024; Ruiying Liu; Chaolong Ying; Ruimao Zhang; Tianshu Yu 001 (CoRR, 2023)

A Multiobjective Evolutionary Approach for Solving Large-Scale Network Reconstruction Problems via Logistic Principal Component Analysis. - Chaolong Ying; Jing Liu 006; Kai Wu 003; Chao Wang 099 (IEEE Trans. Cybern., 2023)

Boosting Graph Pooling with Persistent Homology. - Chaolong Ying; Xinjian Zhao; Tianshu Yu 001 (NeurIPS, 2024)

Graph Learning with Distributional Edge Layouts. - Xinjian Zhao; Chaolong Ying; Tianshu Yu 001 (CoRR, 2024)

Do spectral cues matter in contrast-based graph self-supervised learning? - Xiangru Jian; Xinjian Zhao; Wei Pang; Chaolong Ying; Yimu Wang; Yaoyao Xu; Tianshu Yu 001 (CoRR, 2024)

Rethinking the "Heatmap + Monte Carlo Tree Search" Paradigm for Solving Large Scale TSP. - Xuanhao Pan; Chenguang Wang 011; Chaolong Ying; Ye Xue; Tianshu Yu 001 (CoRR, 2024)

NeuroLifting: Neural Inference on Markov Random Fields at Scale. - Yaomin Wang; Chaolong Ying; Xiaodong Luo; Tianshu Yu 001 (CoRR, 2024)

Graph Learning with Distributional Edge Layouts. - Xinjian Zhao; Chaolong Ying; Yaoyao Xu; Tianshu Yu 001 (KDD (1), 2025)

Rethinking Spectral Augmentation for Contrast-based Graph Self-Supervised Learning. - Xiangru Jian; Xinjian Zhao; Wei Pang; Chaolong Ying; Yimu Wang; Yaoyao Xu; Tianshu Yu 001 (Trans. Mach. Learn. Res., 2025)

Neural Graduated Assignment for Maximum Common Edge Subgraphs. - Chaolong Ying; Yingqi Ruan; Xuemin Chen; Yaomin Wang; Tianshu Yu 001 (CoRR, 2025)