Scientific discovery in the age of artificial intelligence H Wang, T Fu, Y Du, W Gao, K Huang, Z Liu, P Chandak, S Liu, ... Nature 620 (7972), 47-60, 2023 | 346* | 2023 |
DeepPurpose: a deep learning library for drug–target interaction prediction K Huang, T Fu, LM Glass, M Zitnik, C Xiao, J Sun Bioinformatics 36 (22-23), 5545-5547, 2020 | 305 | 2020 |
Therapeutics data Commons: machine learning datasets and tasks for therapeutics K Huang, T Fu, W Gao, Y Zhao, Y Roohani, J Leskovec, CW Coley, ... NeurIPS Datasets and Benchmarks, 2021 | 213* | 2021 |
Deep feature for text-dependent speaker verification Y Liu, Y Qian, N Chen, T Fu, Y Zhang, K Yu Speech Communication 73, 1-13, 2015 | 209 | 2015 |
Artificial intelligence foundation for therapeutic science K Huang, T Fu, W Gao, Y Zhao, Y Roohani, J Leskovec, CW Coley, ... Nature Chemical Biology, 2022 | 83 | 2022 |
Sample efficiency matters: a benchmark for practical molecular optimization W Gao, T Fu, J Sun, C Coley Advances in Neural Information Processing Systems 35, 21342-21357, 2022 | 76 | 2022 |
MIMOSA: Multi-constraint molecule sampling for molecule optimization T Fu, C Xiao, X Li, LM Glass, J Sun Proceedings of the AAAI Conference on Artificial Intelligence 35 (1), 125-133, 2021 | 66 | 2021 |
Machine learning for synthetic data generation: a review Y Lu, M Shen, H Wang, X Wang, C van Rechem, T Fu, W Wei arXiv preprint arXiv:2302.04062, 2024 | 65 | 2024 |
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design Y Du, T Fu, J Sun, S Liu arXiv preprint arXiv:2203.14500, 2022 | 63 | 2022 |
CORE: Automatic molecule optimization using copy & refine strategy T Fu, C Xiao, J Sun Proceedings of the AAAI Conference on Artificial Intelligence 34 (01), 638-645, 2020 | 61 | 2020 |
Differentiable scaffolding tree for molecular optimization T Fu, W Gao, C Xiao, J Yasonik, CW Coley, J Sun The International Conference on Learning Representations (ICLR), 2022 | 57 | 2022 |
Speaker verification with deep features. Y Liu, T Fu, Y Fan, Y Qian, K Yu IJCNN, 747-753, 2014 | 51 | 2014 |
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems X Zhang, L Wang, J Helwig, Y Luo, C Fu, Y Xie, M Liu, Y Lin, Z Xu, K Yan, ... arXiv preprint arXiv:2307.08423, 2023 | 46 | 2023 |
Tandem deep features for text-dependent speaker verification T Fu, Y Qian, Y Liu, K Yu Fifteenth Annual Conference of the International Speech Communication …, 2014 | 39 | 2014 |
Reinforced genetic algorithm for structure-based drug design T Fu, W Gao, C Coley, J Sun Advances in Neural Information Processing Systems 35, 12325-12338, 2022 | 36 | 2022 |
Hint: Hierarchical interaction network for clinical-trial-outcome predictions T Fu, K Huang, C Xiao, LM Glass, J Sun Patterns 3 (4), 2022 | 33 | 2022 |
DDL: deep dictionary learning for predictive phenotyping T Fu, TN Hoang, C Xiao, J Sun Proceedings of the 28th International Joint Conference on Artificial …, 2019 | 27 | 2019 |
An improved i-vector extraction algorithm for speaker verification W Li, T Fu, J Zhu EURASIP Journal on Audio, Speech, and Music Processing 2015 (1), 18, 2015 | 23 | 2015 |
CPSG-MCMC: Clustering-Based Preprocessing method for Stochastic Gradient MCMC T Fu, Z Zhang Artificial Intelligence and Statistics, 841-850, 2017 | 22 | 2017 |
Probabilistic and Dynamic Molecule-Disease Interaction Modeling for Drug Discovery T Fu, C Xiao, C Qian, LM Glass, J Sun Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 20 | 2021 |