Yaosen Min

Beijing Academy of Artificial Intelligence — China

Computer Science · Physical Sciences

7h-index493citations32works7.92yr avg
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Research Topics

Computational Drug Discovery Methods(14), Protein Structure and Dynamics(10), Machine Learning in Materials Science(10), Bioinformatics and Genomic Networks(6), Advanced Graph Neural Networks(5)

Publications32 total

ProMeta: A meta-learning framework for robust disease diagnosis and prediction from plasma proteomics
2026Open Access
Multi-scale Graph Autoregressive Modeling: Molecular Property Prediction via Next Token Prediction
ArXiv.org·2026Open Access
Multi-scale Graph Autoregressive Modeling: Molecular Property Prediction via Next Token Prediction
arXiv (Cornell University)·2026Open Access
PRSNet-2: End-to-end genotype-to-phenotype prediction via hierarchical graph neural networks
2025Open Access
ImagebindDC: Compressing Multi-modal Data with Imagebind-based Condensation
arXiv (Cornell University)·2025Open Access
MIPS: A Multimodal Infinite Polymer Sequence Pre-training Framework for Polymer Property Prediction
2025Open Access
FlexRibbon: Joint Sequence and Structure Pretraining for Protein Modeling
2025Open Access
CellNavi predicts genes directing cellular transitions by learning a gene graph-enhanced cell state manifold
Nature Cell Biology·2025Open Access
Illuminating the Virosphere’s Dark Matter using Hierarchical Deep Learning
2025Open Access
STARNet enables spatially resolved inference of gene regulatory networks from spatial multi-omics data
2025· 1 citedOpen Access
Controlling risks of AI in chemical science with agents
AI for Science·2025· 1 citedOpen Access
Nature Language Model: Deciphering the Language of Nature for Scientific Discovery
arXiv (Cornell University)·2025· 1 citedOpen Access
SFM-Protein: Integrative Co-evolutionary Pre-training for Advanced Protein Sequence Representation
arXiv (Cornell University)·2024· 1 citedOpen Access
Directing cellular transitions on gene graph-enhanced cell state manifold
2024Open Access
Author Correction: Predicting equilibrium distributions for molecular systems with deep learning
Nature Machine Intelligence·2024· 1 citedOpen Access
From Static to Dynamic Structures: Improving Binding Affinity Prediction with Graph‐Based Deep Learning
Advanced Science·2024· 20 citedOpen Access
Predicting equilibrium distributions for molecular systems with deep learning
Nature Machine Intelligence·2024· 110 citedOpen Access
Control Risk for Potential Misuse of Artificial Intelligence in Science
arXiv (Cornell University)·2023· 6 citedOpen Access
A knowledge-guided pre-training framework for improving molecular representation learning
Nature Communications·2023· 115 citedOpen Access
Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning
arXiv (Cornell University)·2023· 30 citedOpen Access
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Frequent Co-authors

Haiguang Liu(9), Shuxin Zheng(8), Yingheng Wang(6), Ji Wu(6), Han Li(6), Jiyan He(6), Fusong Ju(6), Jianyang Zeng(5), Weitao Feng(5), Peiran Jin(5), Hongxia Hao(4), Tie‐Yan Liu(4), Xuefeng Cui(4), Yu Shi(3), Ziheng Lu(3), Jiaxi Wang(3), Jianwei Zhu(3), Chi Chen(3), Frank Noé(3), Tie‐Yan Liu(3)