Yaochen Xie

Mitchell Institute — United States

Materials Science · Physical Sciences

12h-index1.6kcitations41works4.42yr avg
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Research Topics

Machine Learning in Materials Science(11), Advanced Graph Neural Networks(9), Computational Drug Discovery Methods(7), Image Processing Techniques and Applications(7), Topic Modeling(6)

Publications41 total

Can LLM Agents Simulate Multi-Turn Human Behavior? Evidence from Real Online Customer Behavior Data
ArXiv.org·2025Open Access
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems
Foundations and Trends® in Machine Learning·2025· 6 cited
SimRAG: Self-Improving Retrieval-Augmented Generation for Adapting Large Language Models to Specialized Domains
2025· 3 citedOpen Access
Reasoning with Graphs: Structuring Implicit Knowledge to Enhance LLMs Reasoning
2025· 1 citedOpen Access
Exploring Query Understanding for Amazon Product Search
2024· 2 cited
SimRAG: Self-Improving Retrieval-Augmented Generation for Adapting Large Language Models to Specialized Domains
arXiv (Cornell University)·2024Open Access
Exploring Query Understanding for Amazon Product Search
arXiv (Cornell University)·2024Open Access
Unsupervised deep representation learning enables phenotype discovery for genetic association studies of brain imaging
Communications Biology·2024· 30 citedOpen Access
SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations
arXiv (Cornell University)·2024· 1 citedOpen Access
3D Molecular Geometry Analysis with 2D Graphs
Society for Industrial and Applied Mathematics eBooks·2024· 1 cited
Genetic InfoMax: Exploring Mutual Information Maximization in High-Dimensional Imaging Genetics Studies
PubMed·2023· 3 citedOpen Access
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems
arXiv (Cornell University)·2023· 53 citedOpen Access
3D Molecular Geometry Analysis with 2D Graphs
arXiv (Cornell University)·2023Open Access
Frontiers of Graph Neural Networks with DIG
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining·2022
Augmented Equivariant Attention Networks for Microscopy Image Transformation
IEEE Transactions on Medical Imaging·2022· 2 cited
Self-Supervised Learning of Graph Neural Networks: A Unified Review
IEEE Transactions on Pattern Analysis and Machine Intelligence·2022· 346 citedOpen Access
Advanced graph and sequence neural networks for molecular property prediction and drug discovery
Bioinformatics·2022· 105 cited
Task-Agnostic Graph Explanations
arXiv (Cornell University)·2022· 4 citedOpen Access
Self-Supervised Representation Learning via Latent Graph Prediction
arXiv (Cornell University)·2022· 8 citedOpen Access
Group Contrastive Self-Supervised Learning on Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence·2022· 24 cited
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Frequent Co-authors

Shuiwang Ji(29), Youzhi Luo(11), Xu Zhao(10), Zhengyang Wang(8), Meng Liu(6), Limei Wang(6), Cheng Deng(5), Sreyashi Nag(5), Haiyang Yu(4), Cong Fu(4), Xuan Zhang(4), Xianfeng Tang(4), Jingtun Zhang(3), Shurui Gui(3), Keqiang Yan(3), Xuan Zhang(3), Jacob Helwig(3), Yuchao Lin(3), Shenglong Xu(3), Kaleb Dickerson(3)