Tianfan Fu

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 48

Top Topics

Speaker Verification

Machine Learning

Top Venues

Publications

Chufan Gao, Tianfan Fu, Jimeng Sun
Language Interaction Network for Clinical Trial Approval Estimation. CoRR (2024)
Yoshitaka Inoue, Hunmin Lee, Tianfan Fu, Augustin Luna
drGAT: Attention-Guided Gene Assessment of Drug Response Utilizing a Drug-Cell-Gene Heterogeneous Network. CoRR (2024)
Wenhao Zheng, Dongsheng Peng, Hongxia Xu, Hongtu Zhu, Tianfan Fu, Huaxiu Yao
Multimodal Clinical Trial Outcome Prediction with Large Language Models. CoRR (2024)
Ling Yue, Jonathan Li, Md. Zabirul Islam, Bolun Xia, Tianfan Fu, Jintai Chen
TrialDura: Hierarchical Attention Transformer for Interpretable Clinical Trial Duration Prediction. CoRR (2024)
Xinze Li, Penglei Wang, Tianfan Fu, Wenhao Gao, Chengtao Li, Leilei Shi, Junhong Liu
AUTODIFF: Autoregressive Diffusion Modeling for Structure-based Drug Design. CoRR (2024)
Songtao Liu, Jinghui Chen, Tianfan Fu, Lu Lin, Marinka Zitnik, Dinghao Wu
Graph Adversarial Diffusion Convolution. CoRR (2024)
Ling Yue, Sixue Xing, Jintai Chen, Tianfan Fu
TrialEnroll: Predicting Clinical Trial Enrollment Success with Deep & Cross Network and Large Language Models. CoRR (2024)
Jintai Chen, Yaojun Hu, Yue Wang, Yingzhou Lu, Xu Cao, Miao Lin, Hongxia Xu, Jian Wu, Cao Xiao, Jimeng Sun, Lucas Glass, Kexin Huang, Marinka Zitnik, Tianfan Fu
TrialBench: Multi-Modal Artificial Intelligence-Ready Clinical Trial Datasets. CoRR (2024)
Shenda Hong, Daoxin Yin, Gongzheng Tang, Tianfan Fu, Liantao Ma, Junyi Gao, Mengling Feng, Mai Wang, Yu Yang, Fei Wang, Hongfang Liu, Luxia Zhang
Artificial Intelligence and Data Science for Healthcare: Bridging Data-Centric AI and People-Centric Healthcare. KDD (2024)
Kangyu Zheng, Yingzhou Lu, Zaixi Zhang, Zhongwei Wan, Yao Ma, Marinka Zitnik, Tianfan Fu
Structure-based Drug Design Benchmark: Do 3D Methods Really Dominate? CoRR (2024)
Yuanqi Du, Arian R. Jamasb, Jeff Guo, Tianfan Fu, Charles Harris, Yingheng Wang, Chenru Duan, Pietro Liò, Philippe Schwaller, Tom L. Blundell
Machine learning-aided generative molecular design. Nat. Mac. Intell. 6 (6) (2024)
Ling Yue, Tianfan Fu
CT-Agent: Clinical Trial Multi-Agent with Large Language Model-based Reasoning. CoRR (2024)
Zifeng Wang, Brandon Theodorou, Tianfan Fu, Cao Xiao, Jimeng Sun
PyTrial: A Comprehensive Platform for Artificial Intelligence for Drug Development. CoRR (2023)
Namkyeong Lee, Heewoong Noh, Gyoung S. Na, Tianfan Fu, Jimeng Sun, Chanyoung Park
Stoichiometry Representation Learning with Polymorphic Crystal Structures. CoRR (2023)
Tao Feng, Pengcheng Xu, Tianfan Fu, Siddhartha Laghuvarapu, Jimeng Sun
Molecular De Novo Design through Transformer-based Reinforcement Learning. CoRR (2023)
Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR (2023)
Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, Anima Anandkumar, Karianne Bergen, Carla P. Gomes, Shirley Ho, Pushmeet Kohli, Joan Lasenby, Jure Leskovec, Tie-Yan Liu, Arjun Manrai, Debora S. Marks, Bharath Ramsundar, Le Song, Jimeng Sun, Jian Tang, Petar Velickovic, Max Welling, Linfeng Zhang, Connor W. Coley, Yoshua Bengio, Marinka Zitnik
Scientific discovery in the age of artificial intelligence. Nat. 620 (7972) (2023)
Tianfan Fu, Jimeng Sun
SIPF: Sampling Method for Inverse Protein Folding. KDD (2022)
Tianfan Fu, Jimeng Sun
Antibody Complementarity Determining Regions (CDRs) design using Constrained Energy Model. KDD (2022)
Tianfan Fu, Kexin Huang, Cao Xiao, Lucas M. Glass, Jimeng Sun
HINT: Hierarchical interaction network for clinical-trial-outcome predictions. Patterns 3 (4) (2022)
Tianfan Fu, Cao Xiao, Lucas M. Glass, Jimeng Sun
MOLER: Incorporate Molecule-Level Reward to Enhance Deep Generative Model for Molecule Optimization. IEEE Trans. Knowl. Data Eng. 34 (11) (2022)
Wenhao Gao, Tianfan Fu, Jimeng Sun, Connor W. Coley
Sample Efficiency Matters: A Benchmark for Practical Molecular Optimization. NeurIPS (2022)
Tianfan Fu, Wenhao Gao, Connor W. Coley, Jimeng Sun
Reinforced Genetic Algorithm for Structure-based Drug Design. NeurIPS (2022)
Yuanqi Du, Tianfan Fu, Jimeng Sun, Shengchao Liu
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design. CoRR (2022)
Wenhao Gao, Tianfan Fu, Jimeng Sun, Connor W. Coley
Sample Efficiency Matters: A Benchmark for Practical Molecular Optimization. CoRR (2022)
Tianfan Fu, Wenhao Gao, Connor W. Coley, Jimeng Sun
Reinforced Genetic Algorithm for Structure-based Drug Design. CoRR (2022)
Tianfan Fu, Wenhao Gao, Cao Xiao, Jacob Yasonik, Connor W. Coley, Jimeng Sun
Differentiable Scaffolding Tree for Molecule Optimization. ICLR (2022)
Tianfan Fu, Cao Xiao, Kexin Huang, Lucas M. Glass, Jimeng Sun
SPEAR: self-supervised post-training enhancer for molecule optimization. BCB (2021)
Kexin Huang, Tianfan Fu, Wenhao Gao, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W. Coley, Cao Xiao, Jimeng Sun, Marinka Zitnik
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Therapeutics. CoRR (2021)
Tianfan Fu, Wenhao Gao, Cao Xiao, Jacob Yasonik, Connor W. Coley, Jimeng Sun
Differentiable Scaffolding Tree for Molecular Optimization. CoRR (2021)
Kexin Huang, Tianfan Fu, Lucas M. Glass, Marinka Zitnik, Cao Xiao, Jimeng Sun
DeepPurpose: a deep learning library for drug-target interaction prediction. Bioinform. 36 (22-23) (2021)
Tianfan Fu, Kexin Huang, Cao Xiao, Lucas M. Glass, Jimeng Sun
HINT: Hierarchical Interaction Network for Trial Outcome Prediction Leveraging Web Data. CoRR (2021)
Tianfan Fu, Cao Xiao, Cheng Qian, Lucas M. Glass, Jimeng Sun
Probabilistic and Dynamic Molecule-Disease Interaction Modeling for Drug Discovery. KDD (2021)
Tianfan Fu, Cao Xiao, Xinhao Li, Lucas M. Glass, Jimeng Sun
MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization. AAAI (2021)
Kexin Huang, Tianfan Fu, Wenhao Gao, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W. Coley, Cao Xiao, Jimeng Sun, Marinka Zitnik
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development. NeurIPS Datasets and Benchmarks (2021)
Tianfan Fu, Cao Xiao, Xinhao Li, Lucas M. Glass, Jimeng Sun
MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization. CoRR (2020)
Tianfan Fu, Cao Xiao, Jimeng Sun
CORE: Automatic Molecule Optimization Using Copy & Refine Strategy. AAAI (2020)
Tianfan Fu, Cao Xiao, Lucas M. Glass, Jimeng Sun
α-MOP: Molecule optimization with α-divergence. BIBM (2020)
Kexin Huang, Tianfan Fu, Dawood Khan, Ali Abid, Ali Abdalla, Abubakar Abid, Lucas M. Glass, Marinka Zitnik, Cao Xiao, Jimeng Sun
MolDesigner: Interactive Design of Efficacious Drugs with Deep Learning. CoRR (2020)
Kexin Huang, Tianfan Fu, Cao Xiao, Lucas Glass, Jimeng Sun
DeepPurpose: a Deep Learning Based Drug Repurposing Toolkit. CoRR (2020)
Tianfan Fu, Cao Xiao, Jimeng Sun
CORE: Automatic Molecule Optimization Using Copy & Refine Strategy. CoRR (2019)
Tianfan Fu, Tian Gao, Cao Xiao, Tengfei Ma, Jimeng Sun
PEARL: Prototype Learning via Rule Learning. BCB (2019)
Tianfan Fu, Tian Gao, Cao Xiao, Tengfei Ma, Jimeng Sun
PEARL: Prototype Learning via Rule Learning. BCB (2019)
Tianfan Fu, Trong Nghia Hoang, Cao Xiao, Jimeng Sun
DDL: Deep Dictionary Learning for Predictive Phenotyping. IJCAI (2019)
Tianfan Fu, Cheng Zhang, Stephan Mandt
Continuous Word Embedding Fusion via Spectral Decomposition. CoNLL (2018)
Tianfan Fu, Zhihua Zhang
CPSG-MCMC: Clustering-Based Preprocessing method for Stochastic Gradient MCMC. AISTATS (2017)
Wei Li, Tianfan Fu, Hanxu You, Jie Zhu, Ning Chen
Feature sparsity analysis for i-vector based speaker verification. Speech Commun. 80 (2016)
Tianfan Fu, Luo Luo, Zhihua Zhang
Quasi-Newton Hamiltonian Monte Carlo. UAI (2016)
Wei Li, Tianfan Fu, Jie Zhu, Ning Chen
Sparsity Analysis and Compensation for i-Vector Based Speaker Verification. SPECOM (2015)
Yuan Liu, Yanmin Qian, Nanxin Chen, Tianfan Fu, Ya Zhang, Kai Yu
Deep feature for text-dependent speaker verification. Speech Commun. 73 (2015)
Wei Li, Tianfan Fu, Jie Zhu
An improved i-vector extraction algorithm for speaker verification. EURASIP J. Audio Speech Music. Process. 2015 (2015)
Tianfan Fu, Yanmin Qian, Yuan Liu, Kai Yu
Tandem deep features for text-dependent speaker verification. INTERSPEECH (2014)
Wei Deng, Yanmin Qian, Yuchen Fan, Tianfan Fu, Kai Yu
Stochastic data sweeping for fast DNN training. ICASSP (2014)
Yuan Liu, Tianfan Fu, Yuchen Fan, Yanmin Qian, Kai Yu
Speaker verification with deep features. IJCNN (2014)