| 2022 | IWCMC | Optimization-driven Deep Reinforcement Learning for Sniffer Patrolling in Wireless Networks. | Xiaoling Luo, Meng Wang, Chunnian Zeng, Chengtao Li, Jing Xu, Shimin Gong |
| 2021 | ICLR | Molecule Optimization by Explainable Evolution. | Binghong Chen, Tianzhe Wang, Chengtao Li, Hanjun Dai, Le Song |
| 2020 | ICML | Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search. | Binghong Chen, Chengtao Li, Hanjun Dai, Le Song |
| 2018 | ECCV | Improving Sequential Determinantal Point Processes for Supervised Video Summarization. | Aidean Sharghi, Ali Borji, Chengtao Li, Tianbao Yang, Boqing Gong |
| 2018 | ICLR | Distributional Adversarial Networks. | Chengtao Li, David Alvarez-Melis, Keyulu Xu, Stefanie Jegelka, Suvrit Sra |
| 2018 | ICML | Representation Learning on Graphs with Jumping Knowledge Networks. | Keyulu Xu, Chengtao Li, Yonglong Tian, Tomohiro Sonobe, Ken-ichi Kawarabayashi, Stefanie Jegelka |
| 2017 | ICLR | Neural Program Lattices. | Chengtao Li, Daniel Tarlow, Alexander L. Gaunt, Marc Brockschmidt, Nate Kushman |
| 2017 | ICML | Batched High-dimensional Bayesian Optimization via Structural Kernel Learning. | Zi Wang, Chengtao Li, Stefanie Jegelka, Pushmeet Kohli |
| 2016 | AISTATS | Efficient Sampling for k-Determinantal Point Processes. | Chengtao Li, Stefanie Jegelka, Suvrit Sra |
| 2016 | ICML | Fast DPP Sampling for Nystrom with Application to Kernel Methods. | Chengtao Li, Stefanie Jegelka, Suvrit Sra |
| 2016 | ICML | Gaussian quadrature for matrix inverse forms with applications. | Chengtao Li, Suvrit Sra, Stefanie Jegelka |
| 2015 | NAACL | Randomized Greedy Inference for Joint Segmentation, POS Tagging and Dependency Parsing. | Yuan Zhang, Chengtao Li, Regina Barzilay, Kareem Darwish |
| 2014 | ICML | Bayesian Max-margin Multi-Task Learning with Data Augmentation. | Chengtao Li, Jun Zhu, Jianfei Chen |
| 2013 | SDM | Sentiment Topic Model with Decomposed Prior. | Zheng Chen, Chengtao Li, Jian-Tao Sun, Jianwen Zhang |