Structured Output Learning with Candidate Labels for Local Parts. - Chengtao Li; Jianwen Zhang; Zheng Chen 001 (ECML/PKDD (2), 2013)

Sentiment Topic Model with Decomposed Prior. - Zheng Chen 001; Chengtao Li; Jian-Tao Sun; Jianwen Zhang (SDM, 2013)

Bayesian Max-margin Multi-Task Learning with Data Augmentation. - Chengtao Li; Jun Zhu 001; Jianfei Chen 001 (ICML, 2014)

Randomized Greedy Inference for Joint Segmentation, POS Tagging and Dependency Parsing. - Yuan Zhang 001; Chengtao Li; Regina Barzilay; Kareem Darwish (HLT-NAACL, 2015)

Bounds on bilinear inverse forms via Gaussian quadrature with applications. - Chengtao Li; Suvrit Sra; Stefanie Jegelka (CoRR, 2015)

Efficient Sampling for k-Determinantal Point Processes. - Chengtao Li; Stefanie Jegelka; Suvrit Sra (AISTATS, 2016)

Fast DPP Sampling for Nystrom with Application to Kernel Methods. - Chengtao Li; Stefanie Jegelka; Suvrit Sra (ICML, 2016)

Gaussian quadrature for matrix inverse forms with applications. - Chengtao Li; Suvrit Sra; Stefanie Jegelka (ICML, 2016)

Fast Mixing Markov Chains for Strongly Rayleigh Measures, DPPs, and Constrained Sampling. - Chengtao Li; Suvrit Sra; Stefanie Jegelka (NIPS, 2016)

Fast Sampling for Strongly Rayleigh Measures with Application to Determinantal Point Processes. - Chengtao Li; Stefanie Jegelka; Suvrit Sra (CoRR, 2016)

A topical diversity-based approach to detecting similar question groups from collaborative question-answering archives. - Tianyong Hao; Chengtao Li; Wanqing Liang; Yingying Qu (Web Intell., 2016)

Neural Program Lattices. - Chengtao Li; Daniel Tarlow; Alexander L. Gaunt; Marc Brockschmidt; Nate Kushman (ICLR (Poster), 2017)

Batched High-dimensional Bayesian Optimization via Structural Kernel Learning. - Zi Wang 004; Chengtao Li; Stefanie Jegelka; Pushmeet Kohli (ICML, 2017)

Polynomial time algorithms for dual volume sampling. - Chengtao Li; Stefanie Jegelka; Suvrit Sra (NIPS, 2017)

Improving Sequential Determinantal Point Processes for Supervised Video Summarization. - Aidean Sharghi; Ali Borji; Chengtao Li; Tianbao Yang; Boqing Gong (ECCV (3), 2018)

Distributional Adversarial Networks. - Chengtao Li; David Alvarez-Melis; Keyulu Xu; Stefanie Jegelka; Suvrit Sra (ICLR (Workshop), 2018)

Representation Learning on Graphs with Jumping Knowledge Networks. - Keyulu Xu; Chengtao Li; Yonglong Tian; Tomohiro Sonobe; Ken-ichi Kawarabayashi; Stefanie Jegelka (ICML, 2018)

Robust GANs against Dishonest Adversaries. - Zhi Xu; Chengtao Li; Stefanie Jegelka (CoRR, 2018)

Retrosynthesis Prediction with Conditional Graph Logic Network. - Hanjun Dai; Chengtao Li; Connor W. Coley; Bo Dai 001; Le Song (NeurIPS, 2019)

Diversity-inducing probability measures for machine learning. - Chengtao Li (2019)

A Method for Image Big Data Utilization: Automated Progress Monitoring Based on Image Data for Large Construction Site. - Chengtao Li; Li Chen; Jiafeng Wang; Tianjian Xia (ICBDS, 2020)

Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search. - Binghong Chen; Chengtao Li; Hanjun Dai; Le Song (ICML, 2020)

Group Contextual Encoding for 3D Point Clouds. - Xu Liu 017; Chengtao Li; Jian Wang 100; Jingbo Wang; Boxin Shi; Xiaodong He 001 (NeurIPS, 2020)

Molecule Optimization by Explainable Evolution. - Binghong Chen; Tianzhe Wang; Chengtao Li; Hanjun Dai; Le Song (ICLR, 2021)

BioNavi-NP: Biosynthesis Navigator for Natural Products. - Shuangjia Zheng; Tao Zeng; Chengtao Li; Binghong Chen; Connor W. Coley; Yuedong Yang; Ruibo Wu (CoRR, 2021)

Molecular Attributes Transfer from Non-Parallel Data. - Shuangjia Zheng; Ying Song; Zhang Pan; Chengtao Li; Le Song; Yuedong Yang (CoRR, 2021)

Influencing Factors Analysis and Prediction Model of Pavement Transverse Crack Based on Big Data. - Yuqin Zhu; Wengang Ma; Ling Cong 002; Chengtao Li; Shixiang Hu (ICBDS, 2022)

Optimization-driven Deep Reinforcement Learning for Sniffer Patrolling in Wireless Networks. - Xiaoling Luo 003; Meng Wang 034; Chunnian Zeng; Chengtao Li; Jing Xu 005; Shimin Gong (IWCMC, 2022)

TANKBind: Trigonometry-Aware Neural NetworKs for Drug-Protein Binding Structure Prediction. - Wei Lu; Qifeng Wu; Jixian Zhang; Jiahua Rao; Chengtao Li; Shuangjia Zheng (NeurIPS, 2022)

Structure-Aware Multimodal Deep Learning for Drug-Protein Interaction Prediction. - Penglei Wang; Shuangjia Zheng; Yize Jiang; Chengtao Li; Junhong Liu; Chang Wen; Atanas Patronov; Dahong Qian; Hongming Chen 001; Yuedong Yang (J. Chem. Inf. Model., 2022)

Accelerated rational PROTAC design via deep learning and molecular simulations. - Shuangjia Zheng; Youhai Tan; Zhenyu Wang; Chengtao Li; Zhiqing Zhang; Xu Sang; Hongming Chen 001; Yuedong Yang (Nat. Mac. Intell., 2022)

Deep Reinforcement Learning for Joint Trajectory Planning, Transmission Scheduling, and Access Control in UAV-Assisted Wireless Sensor Networks. - Xiaoling Luo 003; Che Chen; Chunnian Zeng; Chengtao Li; Jing Xu 005; Shimin Gong (Sensors, 2023)

STRsensor: a computationally efficient method for STR allele-typing from massively parallel sequencing data. - Xiaolong Zhang; Xianchao Ji; Lingxiang Wang; Lianjiang Chi; Chengtao Li; Shaoqing Wen; Hua Chen 010 (Briefings Bioinform., 2024)

AUTODIFF: Autoregressive Diffusion Modeling for Structure-based Drug Design. - Xinze Li; Penglei Wang; Tianfan Fu; Wenhao Gao 001; Chengtao Li; Leilei Shi; Junhong Liu (CoRR, 2024)