Chengtao Li
Chengtao Li
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Representation learning on graphs with jumping knowledge networks
K Xu, C Li, Y Tian, T Sonobe, K Kawarabayashi, S Jegelka
International conference on machine learning, 5453-5462, 2018
Retrosynthesis prediction with conditional graph logic network
H Dai, C Li, C Coley, B Dai, L Song
Advances in Neural Information Processing Systems 32, 2019
Batched high-dimensional bayesian optimization via structural kernel learning
Z Wang, C Li, S Jegelka, P Kohli
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
Tankbind: Trigonometry-aware neural networks for drug-protein binding structure prediction
W Lu, Q Wu, J Zhang, J Rao, C Li, S Zheng
Advances in neural information processing systems 35, 7236-7249, 2022
Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search
B Chen, C Li, H Dai, L Song
International Conference on Machine Learning, 1608-1616, 2020
Fast dpp sampling for nystrom with application to kernel methods
C Li, S Jegelka, S Sra
International Conference on Machine Learning, 2061-2070, 2016
Efficient sampling for k-determinantal point processes
C Li, S Jegelka, S Sra
Artificial Intelligence and Statistics, 1328-1337, 2016
Randomized greedy inference for joint segmentation, POS tagging and dependency parsing
Y Zhang, C Li, R Barzilay, K Darwish
Proceedings of the 2015 Conference of the North American Chapter of the …, 2015
Improving Sequential Determinantal Point Processes for Supervised Video Summarization
A Sharghi, A Borji, C Li, T Yang, B Gong
Proceedings of the European Conference on Computer Vision (ECCV), 517-533, 2018
Deep learning driven biosynthetic pathways navigation for natural products with BioNavi-NP
S Zheng, T Zeng, C Li, B Chen, CW Coley, Y Yang, R Wu
Nature Communications 13 (1), 3342, 2022
Accelerated rational PROTAC design via deep learning and molecular simulations
S Zheng, Y Tan, Z Wang, C Li, Z Zhang, X Sang, H Chen, Y Yang
Nature Machine Intelligence 4 (9), 739-748, 2022
Fast Mixing Markov Chains for Strongly Rayleigh Measures, DPPs, and Constrained Sampling
C Li, S Sra, S Jegelka
Advances in Neural Information Processing Systems, 4188-4196, 2016
Distributional Adversarial Networks
C Li, D Alvarez-Melis, K Xu, S Jegelka, S Sra
arXiv preprint arXiv:1706.09549, 2017
Polynomial time algorithms for dual volume sampling
C Li, S Jegelka, S Sra
Advances in Neural Information Processing Systems 30, 2017
Structure-aware multimodal deep learning for drug–protein interaction prediction
P Wang, S Zheng, Y Jiang, C Li, J Liu, C Wen, A Patronov, D Qian, ...
Journal of chemical information and modeling 62 (5), 1308-1317, 2022
Neural program lattices
C Li, D Tarlow, AL Gaunt, M Brockschmidt, N Kushman
International conference on learning representations, 2016
Sentiment topic model with decomposed prior
C Li, J Zhang, JT Sun, Z Chen
Proceedings of the 2013 SIAM International Conference on Data Mining, 767-775, 2013
Gaussian quadrature for matrix inverse forms with applications
C Li, S Sra, S Jegelka
International Conference on Machine Learning, 1766-1775, 2016
Bayesian max-margin multi-task learning with data augmentation
C Li, J Zhu, J Chen
International Conference on Machine Learning, 415-423, 2014
Structured output learning with candidate labels for local parts
C Li, J Zhang, Z Chen
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2013
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