The Synthesizability of Molecules Proposed by Generative Models. - Wenhao Gao 001; Connor W. Coley (J. Chem. Inf. Model., 2020)

Deep Learning in Protein Structural Modeling and Design. - Wenhao Gao 001; Sai Pooja Mahajan; Jeremias Sulam; Jeffrey J. Gray (Patterns, 2020)

Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development. - Kexin Huang; Tianfan Fu; Wenhao Gao 001; Yue Zhao 016; Yusuf H. Roohani; Jure Leskovec; Connor W. Coley; Cao Xiao; Jimeng Sun 001; Marinka Zitnik (NeurIPS Datasets and Benchmarks, 2021)

Therapeutics Data Commons: Machine Learning Datasets and Tasks for Therapeutics. - Kexin Huang; Tianfan Fu; Wenhao Gao 001; Yue Zhao 016; Yusuf H. Roohani; Jure Leskovec; Connor W. Coley; Cao Xiao; Jimeng Sun 001; Marinka Zitnik (CoRR, 2021)

Differentiable Scaffolding Tree for Molecular Optimization. - Tianfan Fu; Wenhao Gao 001; Cao Xiao; Jacob Yasonik; Connor W. Coley; Jimeng Sun 001 (CoRR, 2021)

Pairwise Difference Regression: A Machine Learning Meta-algorithm for Improved Prediction and Uncertainty Quantification in Chemical Search. - Michael Tynes; Wenhao Gao 001; Daniel J. Burrill; Enrique R. Batista; Danny Perez; Ping Yang; Nicholas Lubbers (J. Chem. Inf. Model., 2021)

Differentiable Scaffolding Tree for Molecule Optimization. - Tianfan Fu; Wenhao Gao 001; Cao Xiao; Jacob Yasonik; Connor W. Coley; Jimeng Sun 001 (ICLR, 2022)

Amortized Tree Generation for Bottom-up Synthesis Planning and Synthesizable Molecular Design. - Wenhao Gao 001; Rocío Mercado; Connor W. Coley (ICLR, 2022)

Sample Efficiency Matters: A Benchmark for Practical Molecular Optimization. - Wenhao Gao 001; Tianfan Fu; Jimeng Sun 001; Connor W. Coley (NeurIPS, 2022)

Reinforced Genetic Algorithm for Structure-based Drug Design. - Tianfan Fu; Wenhao Gao 001; Connor W. Coley; Jimeng Sun 001 (NeurIPS, 2022)

Scientific discovery in the age of artificial intelligence. - Hanchen Wang 002; Tianfan Fu; Yuanqi Du; Wenhao Gao 001; Kexin Huang; Ziming Liu; Payal Chandak; Shengchao Liu; Peter Van Katwyk; Andreea Deac; Anima Anandkumar; Karianne Bergen; et al. (Nat., 2023)

Projecting Molecules into Synthesizable Chemical Spaces. - Shitong Luo; Wenhao Gao 001; Zuofan Wu; Jian Peng 001; Connor W. Coley; Jianzhu Ma (ICML, 2024)

Double-Ended Synthesis Planning with Goal-Constrained Bidirectional Search. - Kevin Yu; Jihye Roh; Ziang Li; Wenhao Gao 001; Runzhong Wang; Connor W. Coley (NeurIPS, 2024)

Substrate Scope Contrastive Learning: Repurposing Human Bias to Learn Atomic Representations. - Wenhao Gao 001; Priyanka Raghavan; Ron Shprints; Connor W. Coley (CoRR, 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)

Efficient Evolutionary Search Over Chemical Space with Large Language Models. - Haorui Wang; Marta Skreta; Cher Tian Ser; Wenhao Gao 001; Lingkai Kong; Felix Streith-Kalthoff; Chenru Duan; Yuchen Zhuang; Yue Yu 001; Yanqiao Zhu 001; Yuanqi Du; Alán Aspuru-Guzik; et al. (CoRR, 2024)

Syntax-Guided Procedural Synthesis of Molecules. - Michael Sun; Alston Lo; Wenhao Gao 001; Minghao Guo; Veronika Thost; Jie Chen 007; Connor W. Coley; Wojciech Matusik (CoRR, 2024)

Generative Artificial Intelligence for Navigating Synthesizable Chemical Space. - Wenhao Gao 001; Shitong Luo; Connor W. Coley (CoRR, 2024)

Efficient Evolutionary Search Over Chemical Space with Large Language Models. - Haorui Wang; Marta Skreta; Cher Tian Ser; Wenhao Gao 001; Lingkai Kong; Felix Strieth-Kalthoff; Chenru Duan; Yuchen Zhuang; Yue Yu 001; Yanqiao Zhu 001; Yuanqi Du; Alán Aspuru-Guzik; et al. (ICLR, 2025)