Latent Feature Group Learning for High-Dimensional Data Clustering. - Wenting Wang; Yulin He; Liheng Ma; Joshua Zhexue Huang (Inf., 2019)

Memory Augmented Graph Neural Networks for Sequential Recommendation. - Chen Ma 001; Liheng Ma; Yingxue Zhang 001; Jianing Sun; Xue Liu 001; Mark Coates (AAAI, 2020)

Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation. - Chen Ma 001; Liheng Ma; Yingxue Zhang 001; Ruiming Tang; Xue Liu 001; Mark Coates (KDD, 2020)

A new approach to solve opinion dynamics on complex networks. - Wenting Wang; Yu-Lin He; Joshua Zhexue Huang; Liheng Ma (Expert Syst. Appl., 2020)

Soft Tissue Mass of Extremity: Investigation of MRI Diagnostic Strategy. - Yuying Liang; Liheng Ma; Ning Yang; Weifeng Hong; Zhen Wu (J. Medical Imaging Health Informatics, 2020)

Knowledge-Enhanced Top-K Recommendation in Poincaré Ball. - Chen Ma 001; Liheng Ma; Yingxue Zhang 001; Haolun Wu; Xue Liu 001; Mark Coates (AAAI, 2021)

Detection and Defense of Topological Adversarial Attacks on Graphs. - Yingxue Zhang 001; Florence Regol; Soumyasundar Pal; Sakif Khan; Liheng Ma; Mark Coates (AISTATS, 2021)

RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting. - Soumyasundar Pal; Liheng Ma; Yingxue Zhang 001; Mark Coates (ICML, 2021)

Graph Attention Networks with Positional Embeddings. - Liheng Ma; Reihaneh Rabbany; Adriana Romero-Soriano (PAKDD (1), 2021)

Graph Inductive Biases in Transformers without Message Passing. - Liheng Ma; Chen Lin 003; Derek Lim; Adriana Romero-Soriano; Puneet K. Dokania; Mark Coates; Philip H. S. Torr; Ser-Nam Lim (ICML, 2023)

Multi-resolution Time-Series Transformer for Long-term Forecasting. - Yitian Zhang; Liheng Ma; Soumyasundar Pal; Yingxue Zhang 001; Mark Coates (AISTATS, 2024)

CKGConv: General Graph Convolution with Continuous Kernels. - Liheng Ma; Soumyasundar Pal; Yitian Zhang; Jiaming Zhou; Yingxue Zhang 001; Mark Coates (ICML, 2024)

Revealing Decurve Flows for Generalized Graph Propagation. - Chen Lin 003; Liheng Ma; Yiyang Chen; Wanli Ouyang; Michael M. Bronstein; Philip H. S. Torr (CoRR, 2024)

The Heterophilic Graph Learning Handbook: Benchmarks, Models, Theoretical Analysis, Applications and Challenges. - Sitao Luan; Chenqing Hua; Qincheng Lu; Liheng Ma; Lirong Wu; Xinyu Wang; Minkai Xu; Xiao-Wen Chang; Doina Precup; Rex Ying; Stan Z. Li; Jian Tang 005; et al. (CoRR, 2024)

Enhancing Logical Reasoning in Large Language Models through Graph-based Synthetic Data. - Jiaming Zhou; Abbas Ghaddar; Ge Zhang; Liheng Ma; Yaochen Hu 001; Soumyasundar Pal; Mark Coates; Bin Wang 034; Yingxue Zhang 001; Jianye Hao (CoRR, 2024)

Attitude Correlated Frames Based Calibration Method for Star Sensors. - Liheng Ma; Shenglong Xiao; Wenjun Tang; Xiao Luo; Su Zhang (Sensors, 2024)

Sparse Decomposition of Graph Neural Networks. - Yaochen Hu 001; Mai Zeng; Ge Zhang; Pavel Rumiantsev; Liheng Ma; Yingxue Zhang 001; Mark Coates (Trans. Mach. Learn. Res., 2025)

Simplifying Graph Transformers. - Liheng Ma; Soumyasundar Pal; Yingxue Zhang 001; Philip H. S. Torr; Mark Coates (CoRR, 2025)

Reinforcing Question Answering Agents with Minimalist Policy Gradient Optimization. - Yihong Wu; Liheng Ma; Muzhi Li; Jiaming Zhou; Jianye Hao; Ho-fung Leung; Irwin King; Yingxue Zhang 001; Jian-Yun Nie (CoRR, 2025)

SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting. - Yitian Zhang; Liheng Ma; Antonios Valkanas; Boris N. Oreshkin; Mark Coates (CoRR, 2025)

Omni-Thinker: Scaling Cross-Domain Generalization in LLMs via Multi-Task RL with Hybrid Rewards. - Derek Li; Jiaming Zhou; Amirreza Kazemi; Qianyi Sun; Abbas Ghaddar; Mohammad Ali Alomrani; Liheng Ma; Yu Luo; Dong Li 016; Feng Wen; Jianye Hao; Mark Coates; et al. (CoRR, 2025)

An Entity Linking Agent for Question Answering. - Yajie Luo; Yihong Wu; Muzhi Li; Fengran Mo; Jia Ao Sun; Xinyu Wang; Liheng Ma; Yingxue Zhang 001; Jian-Yun Nie (CoRR, 2025)