Stochastic data sweeping for fast DNN training. - Wei Deng; Yanmin Qian; Yuchen Fan; Tianfan Fu; Kai Yu 004 (ICASSP, 2014)

Speaker verification with deep features. - Yuan Liu; Tianfan Fu; Yuchen Fan; Yanmin Qian; Kai Yu 004 (IJCNN, 2014)

Tandem deep features for text-dependent speaker verification. - Tianfan Fu; Yanmin Qian; Yuan Liu; Kai Yu 004 (INTERSPEECH, 2014)

Sparsity Analysis and Compensation for i-Vector Based Speaker Verification. - Wei Li 071; Tianfan Fu; Jie Zhu 006; Ning Chen 007 (SPECOM, 2015)

An improved i-vector extraction algorithm for speaker verification. - Wei Li 071; Tianfan Fu; Jie Zhu 006 (EURASIP J. Audio Speech Music. Process., 2015)

Deep feature for text-dependent speaker verification. - Yuan Liu; Yanmin Qian; Nanxin Chen; Tianfan Fu; Ya Zhang 002; Kai Yu 004 (Speech Commun., 2015)

Quasi-Newton Hamiltonian Monte Carlo. - Tianfan Fu; Luo Luo; Zhihua Zhang 004 (UAI, 2016)

Feature sparsity analysis for i-vector based speaker verification. - Wei Li 071; Tianfan Fu; Hanxu You; Jie Zhu 006; Ning Chen 007 (Speech Commun., 2016)

CPSG-MCMC: Clustering-Based Preprocessing method for Stochastic Gradient MCMC. - Tianfan Fu; Zhihua Zhang (AISTATS, 2017)

Continuous Word Embedding Fusion via Spectral Decomposition. - Tianfan Fu; Cheng Zhang 005; Stephan Mandt (CoNLL, 2018)

PEARL: Prototype Learning via Rule Learning. - Tianfan Fu; Tian Gao; Cao Xiao; Tengfei Ma 001; Jimeng Sun 001 (BCB, 2019)

DDL: Deep Dictionary Learning for Predictive Phenotyping. - Tianfan Fu; Trong Nghia Hoang; Cao Xiao; Jimeng Sun 001 (IJCAI, 2019)

CORE: Automatic Molecule Optimization Using Copy & Refine Strategy. - Tianfan Fu; Cao Xiao; Jimeng Sun 001 (AAAI, 2020)

α-MOP: Molecule optimization with α-divergence. - Tianfan Fu; Cao Xiao; Lucas M. Glass; Jimeng Sun 001 (BIBM, 2020)

DeepPurpose: a Deep Learning Based Drug Repurposing Toolkit. - Kexin Huang; Tianfan Fu; Cao Xiao; Lucas Glass; Jimeng Sun 001 (CoRR, 2020)

MolDesigner: Interactive Design of Efficacious Drugs with Deep Learning. - Kexin Huang; Tianfan Fu; Dawood Khan; Ali Abid; Ali Abdalla; Abubakar Abid; Lucas M. Glass; Marinka Zitnik; Cao Xiao; Jimeng Sun 001 (CoRR, 2020)

MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization. - Tianfan Fu; Cao Xiao; Xinhao Li 001; Lucas M. Glass; Jimeng Sun 001 (AAAI, 2021)

SPEAR: self-supervised post-training enhancer for molecule optimization. - Tianfan Fu; Cao Xiao; Kexin Huang; Lucas M. Glass; Jimeng Sun 001 (BCB, 2021)

Probabilistic and Dynamic Molecule-Disease Interaction Modeling for Drug Discovery. - Tianfan Fu; Cao Xiao; Cheng Qian 001; Lucas M. Glass; Jimeng Sun 001 (KDD, 2021)

Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development. - Kexin Huang; Tianfan Fu; Wenhao Gao 001; Yue Zhao 016; Yusuf H. Roohani; Jure Leskovec; Connor W. Coley; Cao Xiao; Jimeng Sun 001; Marinka Zitnik (NeurIPS Datasets and Benchmarks, 2021)

DeepPurpose: a deep learning library for drug-target interaction prediction. - Kexin Huang; Tianfan Fu; Lucas M. Glass; Marinka Zitnik; Cao Xiao; Jimeng Sun 001 (Bioinform., 2021)

HINT: Hierarchical Interaction Network for Trial Outcome Prediction Leveraging Web Data. - Tianfan Fu; Kexin Huang; Cao Xiao; Lucas M. Glass; Jimeng Sun 001 (CoRR, 2021)

Therapeutics Data Commons: Machine Learning Datasets and Tasks for Therapeutics. - Kexin Huang; Tianfan Fu; Wenhao Gao 001; Yue Zhao 016; Yusuf H. Roohani; Jure Leskovec; Connor W. Coley; Cao Xiao; Jimeng Sun 001; Marinka Zitnik (CoRR, 2021)

Differentiable Scaffolding Tree for Molecular Optimization. - Tianfan Fu; Wenhao Gao 001; Cao Xiao; Jacob Yasonik; Connor W. Coley; Jimeng Sun 001 (CoRR, 2021)

Differentiable Scaffolding Tree for Molecule Optimization. - Tianfan Fu; Wenhao Gao 001; Cao Xiao; Jacob Yasonik; Connor W. Coley; Jimeng Sun 001 (ICLR, 2022)

SIPF: Sampling Method for Inverse Protein Folding. - Tianfan Fu; Jimeng Sun 001 (KDD, 2022)

Antibody Complementarity Determining Regions (CDRs) design using Constrained Energy Model. - Tianfan Fu; Jimeng Sun 001 (KDD, 2022)

Sample Efficiency Matters: A Benchmark for Practical Molecular Optimization. - Wenhao Gao 001; Tianfan Fu; Jimeng Sun 001; Connor W. Coley (NeurIPS, 2022)

Reinforced Genetic Algorithm for Structure-based Drug Design. - Tianfan Fu; Wenhao Gao 001; Connor W. Coley; Jimeng Sun 001 (NeurIPS, 2022)

MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design. - Yuanqi Du; Tianfan Fu; Jimeng Sun 001; Shengchao Liu (CoRR, 2022)

HINT: Hierarchical interaction network for clinical-trial-outcome predictions. - Tianfan Fu; Kexin Huang; Cao Xiao; Lucas M. Glass; Jimeng Sun 001 (Patterns, 2022)

MOLER: Incorporate Molecule-Level Reward to Enhance Deep Generative Model for Molecule Optimization. - Tianfan Fu; Cao Xiao; Lucas M. Glass; Jimeng Sun 001 (IEEE Trans. Knowl. Data Eng., 2022)

PyTrial: A Comprehensive Platform for Artificial Intelligence for Drug Development. - Zifeng Wang 008; Brandon Theodorou; Tianfan Fu; Cao Xiao; Jimeng Sun 001 (CoRR, 2023)

Molecular De Novo Design through Transformer-based Reinforcement Learning. - Tao Feng; Pengcheng Xu; Tianfan Fu; Siddhartha Laghuvarapu; Jimeng Sun 001 (CoRR, 2023)

Stoichiometry Representation Learning with Polymorphic Crystal Structures. - Namkyeong Lee; Heewoong Noh; Gyoung S. Na; Tianfan Fu; Jimeng Sun 001; Chanyoung Park 001 (CoRR, 2023)

Scientific discovery in the age of artificial intelligence. - Hanchen Wang 002; Tianfan Fu; Yuanqi Du; Wenhao Gao 001; Kexin Huang; Ziming Liu; Payal Chandak; Shengchao Liu; Peter Van Katwyk; Andreea Deac; Anima Anandkumar; Karianne Bergen; et al. (Nat., 2023)

Deep Generative Models for Drug Design. - Tianfan Fu (2023)

TrialDura: Hierarchical Attention Transformer for Interpretable Clinical Trial Duration Prediction. - Ling Yue; Sixue Xing; Jonathan Li 010; Md. Zabirul Islam; Bolun Xia; Jintai Chen; Tianfan Fu (BCB, 2024)

ClinicalAgent: Clinical Trial Multi-Agent System with Large Language Model-based Reasoning. - Ling Yue; Sixue Xing; Jintai Chen; Tianfan Fu (BCB, 2024)

TrialEnroll: Predicting Clinical Trial Enrollment Success with Deep & Cross Network and Large Language Models. - Ling Yue; Sixue Xing; Jintai Chen; Tianfan Fu (BCB, 2024)

Graph Adversarial Diffusion Convolution. - Songtao Liu; Jinghui Chen; Tianfan Fu; Lu Lin 001; Marinka Zitnik; Dinghao Wu (ICML, 2024)

Artificial Intelligence and Data Science for Healthcare: Bridging Data-Centric AI and People-Centric Healthcare. - Shenda Hong; Daoxin Yin; Gongzheng Tang; Tianfan Fu; Liantao Ma; Junyi Gao; Mengling Feng; Mai Wang; Yu Yang; Fei Wang 001; Hongfang Liu; Luxia Zhang (KDD, 2024)

Multimodal Clinical Trial Outcome Prediction with Large Language Models. - Wenhao Zheng; Dongsheng Peng; Hongxia Xu; Hongtu Zhu; Tianfan Fu; Huaxiu Yao (CoRR, 2024)

AUTODIFF: Autoregressive Diffusion Modeling for Structure-based Drug Design. - Xinze Li; Penglei Wang; Tianfan Fu; Wenhao Gao 001; Chengtao Li; Leilei Shi; Junhong Liu (CoRR, 2024)

TrialDura: Hierarchical Attention Transformer for Interpretable Clinical Trial Duration Prediction. - Ling Yue; Jonathan Li 010; Md. Zabirul Islam; Bolun Xia; Tianfan Fu; Jintai Chen (CoRR, 2024)

CT-Agent: Clinical Trial Multi-Agent with Large Language Model-based Reasoning. - Ling Yue; Tianfan Fu (CoRR, 2024)

Language Interaction Network for Clinical Trial Approval Estimation. - Chufan Gao; Tianfan Fu; Jimeng Sun 001 (CoRR, 2024)

drGAT: Attention-Guided Gene Assessment of Drug Response Utilizing a Drug-Cell-Gene Heterogeneous Network. - Yoshitaka Inoue; Hunmin Lee; Tianfan Fu; Augustin Luna (CoRR, 2024)

Structure-based Drug Design Benchmark: Do 3D Methods Really Dominate? - Kangyu Zheng; Yingzhou Lu; Zaixi Zhang; Zhongwei Wan; Yao Ma; Marinka Zitnik; Tianfan Fu (CoRR, 2024)

TrialBench: Multi-Modal Artificial Intelligence-Ready Clinical Trial Datasets. - Jintai Chen; Yaojun Hu; Yue Wang; Yingzhou Lu; Xu Cao; Miao Lin; Hongxia Xu; Jian Wu 001; Cao Xiao; Jimeng Sun 001; Lucas Glass; Kexin Huang; et al. (CoRR, 2024)

BioMamba: A Pre-trained Biomedical Language Representation Model Leveraging Mamba. - Ling Yue; Sixue Xing; Yingzhou Lu; Tianfan Fu (CoRR, 2024)

SMILES-Mamba: Chemical Mamba Foundation Models for Drug ADMET Prediction. - Bohao Xu; Yingzhou Lu; Chenhao Li; Ling Yue; Xiao Wang; Nan Hao; Tianfan Fu; Jim Chen (CoRR, 2024)

DrugAgent: Explainable Drug Repurposing Agent with Large Language Model-based Reasoning. - Yoshitaka Inoue; Tianci Song; Tianfan Fu (CoRR, 2024)

Quantum-machine-assisted Drug Discovery: Survey and Perspective. - Yidong Zhou; Jintai Chen; Jinglei Cheng; Gopal Karemore; Marinka Zitnik; Frederic T. Chong; Junyu Liu; Tianfan Fu; Zhiding Liang (CoRR, 2024)

Quantum-inspired Reinforcement Learning for Synthesizable Drug Design. - Dannong Wang; Jintai Chen; Zhiding Liang; Tianfan Fu; Xiao-Yang Liu (CoRR, 2024)

Protein-Mamba: Biological Mamba Models for Protein Function Prediction. - Bohao Xu; Yingzhou Lu; Yoshitaka Inoue; Namkyeong Lee; Tianfan Fu; Jintai Chen (CoRR, 2024)

DeepProtein: Deep Learning Library and Benchmark for Protein Sequence Learning. - Jiaqing Xie; Yue Zhao; Tianfan Fu (CoRR, 2024)

Retrieval-Reasoning Large Language Model-based Synthetic Clinical Trial Generation. - Zerui Xu; Fang Wu; Tianfan Fu; Yue Zhao 016 (CoRR, 2024)

DrugAgent: Automating AI-aided Drug Discovery Programming through LLM Multi-Agent Collaboration. - Sizhe Liu; Yizhou Lu; Siyu Chen; Xiyang Hu; Jieyu Zhao 001; Tianfan Fu; Yue Zhao 016 (CoRR, 2024)

3D Interaction Geometric Pre-training for Molecular Relational Learning. - Namkyeong Lee; Yunhak Oh; Heewoong Noh; Gyoung S. Na; Minkai Xu; Hanchen Wang 002; Tianfan Fu; Chanyoung Park 001 (CoRR, 2024)

Political-LLM: Large Language Models in Political Science. - Lincan Li; Jiaqi Li; Catherine Chen 003; Fred Gui; Hongjia Yang; Chenxiao Yu; Zhengguang Wang; Jianing Cai; Junlong Aaron Zhou; Bolin Shen; Alex Qian; Weixin Chen; et al. (CoRR, 2024)

FinLoRA: Finetuning Quantized Financial Large Language Models Using Low-Rank Adaptation. - Dannong Wang; Daniel Kim; Bo Jin; Xingjian Zhao; Tianfan Fu; Steve Yang; Xiao-Yang Liu (CoRR, 2024)

Machine learning-aided generative molecular design. - Yuanqi Du; Arian R. Jamasb; Jeff Guo; Tianfan Fu; Charles Harris; Yingheng Wang; Chenru Duan; Pietro Liò; Philippe Schwaller; Tom L. Blundell (Nat. Mac. Intell., 2024)

Bi-level Contrastive Learning for Knowledge-Enhanced Molecule Representations. - Pengcheng Jiang; Cao Xiao; Tianfan Fu; Parminder Bhatia; Taha A. Kass-Hout; Jimeng Sun 001; Jiawei Han 001 (AAAI, 2025)

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. - Xuan Zhang; Limei Wang; Jacob Helwig; Youzhi Luo; Cong Fu 003; Yaochen Xie; Meng Liu 015; Yuchao Lin; Zhao Xu 005; Keqiang Yan; Keir Adams; Maurice Weiler; et al. (Found. Trends Mach. Learn., 2025)

A review on knowledge graphs for healthcare: Resources, applications, and promises. - Hejie Cui; Jiaying Lu 001; Ran Xu 002; Shiyu Wang 002; Wenjing Ma; Yue Yu 001; Shaojun Yu; Xuan Kan; Chen Ling 003; Liang Zhao 002; Zhaohui S. Qin; Joyce C. Ho; et al. (J. Biomed. Informatics, 2025)

Reinforcement Learning for Quantum Circuit Design: Using Matrix Representations. - Zhiyuan Wang; Chunlin Feng; Christopher Poon; Lijian Huang; Xingjian Zhao; Yao Ma; Tianfan Fu; Xiao-Yang Liu (CoRR, 2025)

Gradient GA: Gradient Genetic Algorithm for Drug Molecular Design. - Chris Zhuang; Debadyuti Mukherjee; Yingzhou Lu; Tianfan Fu; Ruqi Zhang (CoRR, 2025)

QCS-ADME: Quantum Circuit Search for Drug Property Prediction with Imbalanced Data and Regression Adaptation. - Kangyu Zheng; Tianfan Fu; Zhiding Liang (CoRR, 2025)

Biomedical Foundation Model: A Survey. - Xiangrui Liu; Yuanyuan Zhang; Yingzhou Lu; Changchang Yin; Xiaoling Hu; Xiaoou Liu; Lulu Chen; Sheng Wang; Alexander Rodriguez; Huaxiu Yao; Yezhou Yang; Ping Zhang 016; et al. (CoRR, 2025)

GraphPINE: Graph Importance Propagation for Interpretable Drug Response Prediction. - Yoshitaka Inoue; Tianfan Fu; Augustin Luna (CoRR, 2025)

PoseX: AI Defeats Physics Approaches on Protein-Ligand Cross Docking. - Yize Jiang; Xinze Li; Yuanyuan Zhang; Jin Han; Youjun Xu; Ayush Pandit; Zaixi Zhang; Mengdi Wang; Mengyang Wang; Chong Liu; Guang Yang; Yejin Choi 001; et al. (CoRR, 2025)

Reasoning BO: Enhancing Bayesian Optimization with Long-Context Reasoning Power of LLMs. - Zhuo Yang; Lingli Ge; Dong Han; Tianfan Fu; Yuqiang Li (CoRR, 2025)

ChemMLLM: Chemical Multimodal Large Language Model. - Qian Tan; Dongzhan Zhou; Peng Xia; Wanhao Liu; Wanli Ouyang; Lei Bai 001; Yuqiang Li; Tianfan Fu (CoRR, 2025)

Scientists' First Exam: Probing Cognitive Abilities of MLLM via Perception, Understanding, and Reasoning. - Yuhao Zhou; Yiheng Wang; Xuming He; Ruoyao Xiao; Zhiwei Li; Qiantai Feng; Zijie Guo; Yuejin Yang; Hao Wu; Wenxuan Huang 001; Jiaqi Wei; Dan Si; et al. (CoRR, 2025)

Position: Intelligent Science Laboratory Requires the Integration of Cognitive and Embodied AI. - Sha Zhang 002; Suorong Yang; Tong Xie; Xiangyuan Xue; Zixuan Hu; Rui Li; Wenxi Qu; Zhenfei Yin; Tianfan Fu; Di Hu 001; Andres M. Bran; Nian Ran; et al. (CoRR, 2025)

SpectrumWorld: Artificial Intelligence Foundation for Spectroscopy. - Zhuo Yang; Jiaqing Xie; Shuaike Shen; Daolang Wang; Yeyun Chen; Ben Gao; Shuzhou Sun; Biqing Qi; Dongzhan Zhou; Lei Bai 001; Linjiang Chen; Shufei Zhang; et al. (CoRR, 2025)

QCBench: Evaluating Large Language Models on Domain-Specific Quantitative Chemistry. - Jiaqing Xie; Weida Wang; Ben Gao; Zhuo Yang; Haiyuan Wang; Shufei Zhang; Tianfan Fu; Yuqiang Li (CoRR, 2025)

Chem3DLLM: 3D Multimodal Large Language Models for Chemistry. - Lei Jiang; Shuzhou Sun; Biqing Qi; Yuchen Fu; Xiaohua Xu; Yuqiang Li; Dongzhan Zhou; Tianfan Fu (CoRR, 2025)