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2020 – today
- 2024
[j8]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): 589-604 (2024)- [c23]Songtao Liu, Jinghui Chen, Tianfan Fu, Lu Lin, Marinka Zitnik, Dinghao Wu:
Graph Adversarial Diffusion Convolution. ICML 2024 - [c22]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: 6720-6721 - [i31]Wenhao Zheng, Dongsheng Peng, Hongxia Xu, Hongtu Zhu, Tianfan Fu, Huaxiu Yao:
Multimodal Clinical Trial Outcome Prediction with Large Language Models. CoRR abs/2402.06512 (2024) - [i30]Xinze Li, Penglei Wang, Tianfan Fu, Wenhao Gao, Chengtao Li, Leilei Shi, Junhong Liu:
AUTODIFF: Autoregressive Diffusion Modeling for Structure-based Drug Design. CoRR abs/2404.02003 (2024) - [i29]Ling Yue, Jonathan Li, Md. Zabirul Islam, Bolun Xia, Tianfan Fu, Jintai Chen:
TrialDura: Hierarchical Attention Transformer for Interpretable Clinical Trial Duration Prediction. CoRR abs/2404.13235 (2024) - [i28]Ling Yue, Tianfan Fu:
CT-Agent: Clinical Trial Multi-Agent with Large Language Model-based Reasoning. CoRR abs/2404.14777 (2024) - [i27]Chufan Gao, Tianfan Fu, Jimeng Sun:
Language Interaction Network for Clinical Trial Approval Estimation. CoRR abs/2405.06662 (2024) - [i26]Yoshitaka Inoue, Hunmin Lee, Tianfan Fu, Augustin Luna:
drGAT: Attention-Guided Gene Assessment of Drug Response Utilizing a Drug-Cell-Gene Heterogeneous Network. CoRR abs/2405.08979 (2024) - [i25]Songtao Liu, Jinghui Chen, Tianfan Fu, Lu Lin, Marinka Zitnik, Dinghao Wu:
Graph Adversarial Diffusion Convolution. CoRR abs/2406.02059 (2024) - [i24]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 abs/2406.03403 (2024) - [i23]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 abs/2407.00631 (2024) - [i22]Ling Yue, Sixue Xing, Jintai Chen, Tianfan Fu:
TrialEnroll: Predicting Clinical Trial Enrollment Success with Deep & Cross Network and Large Language Models. CoRR abs/2407.13115 (2024) - [i21]Ling Yue, Sixue Xing, Yingzhou Lu, Tianfan Fu:
BioMamba: A Pre-trained Biomedical Language Representation Model Leveraging Mamba. CoRR abs/2408.02600 (2024) - [i20]Bohao Xu, Yingzhou Lu, Chenhao Li, Ling Yue, Xiao Wang, Nan Hao, Tianfan Fu, Jim Chen:
SMILES-Mamba: Chemical Mamba Foundation Models for Drug ADMET Prediction. CoRR abs/2408.05696 (2024) - [i19]Yoshitaka Inoue, Tianci Song, Tianfan Fu:
DrugAgent: Explainable Drug Repurposing Agent with Large Language Model-based Reasoning. CoRR abs/2408.13378 (2024) - [i18]Yidong Zhou, Jintai Chen, Jinglei Cheng, Gopal Karemore, Marinka Zitnik, Frederic T. Chong, Junyu Liu, Tianfan Fu, Zhiding Liang:
Quantum-machine-assisted Drug Discovery: Survey and Perspective. CoRR abs/2408.13479 (2024) - [i17]Dannong Wang, Jintai Chen, Zhiding Liang, Tianfan Fu, Xiao-Yang Liu:
Quantum-inspired Reinforcement Learning for Synthesizable Drug Design. CoRR abs/2409.09183 (2024) - [i16]Bohao Xu, Yingzhou Lu, Yoshitaka Inoue, Namkyeong Lee, Tianfan Fu, Jintai Chen:
Protein-Mamba: Biological Mamba Models for Protein Function Prediction. CoRR abs/2409.14617 (2024) - [i15]Jiaqing Xie, Yue Zhao, Tianfan Fu:
DeepProtein: Deep Learning Library and Benchmark for Protein Sequence Learning. CoRR abs/2410.02023 (2024) - 2023
- [j7]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): 47-60 (2023) - [i14]Zifeng Wang, Brandon Theodorou, Tianfan Fu, Cao Xiao, Jimeng Sun:
PyTrial: A Comprehensive Platform for Artificial Intelligence for Drug Development. CoRR abs/2306.04018 (2023) - [i13]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 J. 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 abs/2307.08423 (2023) - [i12]Tao Feng, Pengcheng Xu, Tianfan Fu, Siddhartha Laghuvarapu, Jimeng Sun:
Molecular De Novo Design through Transformer-based Reinforcement Learning. CoRR abs/2310.05365 (2023) - [i11]Namkyeong Lee, Heewoong Noh, Gyoung S. Na, Tianfan Fu, Jimeng Sun, Chanyoung Park:
Stoichiometry Representation Learning with Polymorphic Crystal Structures. CoRR abs/2312.13289 (2023) - 2022
- [j6]Tianfan Fu, Kexin Huang, Cao Xiao, Lucas M. Glass, Jimeng Sun:
HINT: Hierarchical interaction network for clinical-trial-outcome predictions. Patterns 3(4): 100445 (2022) - [j5]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): 5459-5471 (2022) - [c21]Tianfan Fu, Wenhao Gao, Cao Xiao, Jacob Yasonik, Connor W. Coley, Jimeng Sun:
Differentiable Scaffolding Tree for Molecule Optimization. ICLR 2022 - [c20]Tianfan Fu, Jimeng Sun:
SIPF: Sampling Method for Inverse Protein Folding. KDD 2022: 378-388 - [c19]Tianfan Fu, Jimeng Sun:
Antibody Complementarity Determining Regions (CDRs) design using Constrained Energy Model. KDD 2022: 389-399 - [c18]Wenhao Gao, Tianfan Fu, Jimeng Sun, Connor W. Coley:
Sample Efficiency Matters: A Benchmark for Practical Molecular Optimization. NeurIPS 2022 - [c17]Tianfan Fu, Wenhao Gao, Connor W. Coley, Jimeng Sun:
Reinforced Genetic Algorithm for Structure-based Drug Design. NeurIPS 2022 - [i10]Yuanqi Du, Tianfan Fu, Jimeng Sun, Shengchao Liu:
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design. CoRR abs/2203.14500 (2022) - [i9]Wenhao Gao, Tianfan Fu, Jimeng Sun, Connor W. Coley:
Sample Efficiency Matters: A Benchmark for Practical Molecular Optimization. CoRR abs/2206.12411 (2022) - [i8]Tianfan Fu, Wenhao Gao, Connor W. Coley, Jimeng Sun:
Reinforced Genetic Algorithm for Structure-based Drug Design. CoRR abs/2211.16508 (2022) - 2021
- [j4]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): 5545-5547 (2021) - [c16]Tianfan Fu, Cao Xiao, Xinhao Li, Lucas M. Glass, Jimeng Sun:
MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization. AAAI 2021: 125-133 - [c15]Tianfan Fu, Cao Xiao, Kexin Huang, Lucas M. Glass, Jimeng Sun:
SPEAR: self-supervised post-training enhancer for molecule optimization. BCB 2021: 27:1-27:10 - [c14]Tianfan Fu, Cao Xiao, Cheng Qian, Lucas M. Glass, Jimeng Sun:
Probabilistic and Dynamic Molecule-Disease Interaction Modeling for Drug Discovery. KDD 2021: 404-414 - [c13]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 - [i7]Tianfan Fu, Kexin Huang, Cao Xiao, Lucas M. Glass, Jimeng Sun:
HINT: Hierarchical Interaction Network for Trial Outcome Prediction Leveraging Web Data. CoRR abs/2102.04252 (2021) - [i6]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 abs/2102.09548 (2021) - [i5]Tianfan Fu, Wenhao Gao, Cao Xiao, Jacob Yasonik, Connor W. Coley, Jimeng Sun:
Differentiable Scaffolding Tree for Molecular Optimization. CoRR abs/2109.10469 (2021) - 2020
- [c12]Tianfan Fu, Cao Xiao, Jimeng Sun:
CORE: Automatic Molecule Optimization Using Copy & Refine Strategy. AAAI 2020: 638-645 - [c11]Tianfan Fu, Cao Xiao, Lucas M. Glass, Jimeng Sun:
α-MOP: Molecule optimization with α-divergence. BIBM 2020: 240-244 - [i4]Kexin Huang, Tianfan Fu, Cao Xiao, Lucas Glass, Jimeng Sun:
DeepPurpose: a Deep Learning Based Drug Repurposing Toolkit. CoRR abs/2004.08919 (2020) - [i3]Tianfan Fu, Cao Xiao, Xinhao Li, Lucas M. Glass, Jimeng Sun:
MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization. CoRR abs/2010.02318 (2020) - [i2]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 abs/2010.03951 (2020)
2010 – 2019
- 2019
- [c10]Tianfan Fu, Tian Gao, Cao Xiao, Tengfei Ma, Jimeng Sun:
PEARL: Prototype Learning via Rule Learning. BCB 2019: 223-232 - [c9]Tianfan Fu, Tian Gao, Cao Xiao, Tengfei Ma, Jimeng Sun:
PEARL: Prototype Learning via Rule Learning. BCB 2019: 542 - [c8]Tianfan Fu, Trong Nghia Hoang, Cao Xiao, Jimeng Sun:
DDL: Deep Dictionary Learning for Predictive Phenotyping. IJCAI 2019: 5857-5863 - [i1]Tianfan Fu, Cao Xiao, Jimeng Sun:
CORE: Automatic Molecule Optimization Using Copy & Refine Strategy. CoRR abs/1912.05910 (2019) - 2018
- [c7]Tianfan Fu, Cheng Zhang, Stephan Mandt:
Continuous Word Embedding Fusion via Spectral Decomposition. CoNLL 2018: 11-20 - 2017
- [c6]Tianfan Fu, Zhihua Zhang:
CPSG-MCMC: Clustering-Based Preprocessing method for Stochastic Gradient MCMC. AISTATS 2017: 841-850 - 2016
- [j3]Wei Li, Tianfan Fu, Hanxu You, Jie Zhu, Ning Chen:
Feature sparsity analysis for i-vector based speaker verification. Speech Commun. 80: 60-70 (2016) - [c5]Tianfan Fu, Luo Luo, Zhihua Zhang:
Quasi-Newton Hamiltonian Monte Carlo. UAI 2016 - 2015
- [j2]Wei Li, Tianfan Fu, Jie Zhu:
An improved i-vector extraction algorithm for speaker verification. EURASIP J. Audio Speech Music. Process. 2015: 18 (2015) - [j1]Yuan Liu, Yanmin Qian, Nanxin Chen, Tianfan Fu, Ya Zhang, Kai Yu:
Deep feature for text-dependent speaker verification. Speech Commun. 73: 1-13 (2015) - [c4]Wei Li, Tianfan Fu, Jie Zhu, Ning Chen:
Sparsity Analysis and Compensation for i-Vector Based Speaker Verification. SPECOM 2015: 381-388 - 2014
- [c3]Wei Deng, Yanmin Qian, Yuchen Fan, Tianfan Fu, Kai Yu:
Stochastic data sweeping for fast DNN training. ICASSP 2014: 240-244 - [c2]Yuan Liu, Tianfan Fu, Yuchen Fan, Yanmin Qian, Kai Yu:
Speaker verification with deep features. IJCNN 2014: 747-753 - [c1]Tianfan Fu, Yanmin Qian, Yuan Liu, Kai Yu:
Tandem deep features for text-dependent speaker verification. INTERSPEECH 2014: 1327-1331
Coauthor Index
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last updated on 2024-11-11 21:22 CET by the dblp team
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