Wenhao Gao

Orcid: 0000-0002-6506-8044

Affiliations:
  • Massachusetts Institue of Technology (MIT), Department of Chemical Engineering, Cambridge, MA, USA
  • Los Alamos National Laboratory, Los Alamos, NM, USA
  • Johns Hopkins University, Department of Chemical and Biomolecular Engineering, Baltimore, MD, USA (former)


According to our database1, Wenhao Gao authored at least 18 papers between 2020 and 2024.

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Bibliography

2024
Generative Artificial Intelligence for Navigating Synthesizable Chemical Space.
CoRR, 2024

Syntax-Guided Procedural Synthesis of Molecules.
CoRR, 2024

Double-Ended Synthesis Planning with Goal-Constrained Bidirectional Search.
CoRR, 2024

Efficient Evolutionary Search Over Chemical Space with Large Language Models.
CoRR, 2024

AUTODIFF: Autoregressive Diffusion Modeling for Structure-based Drug Design.
CoRR, 2024

Substrate Scope Contrastive Learning: Repurposing Human Bias to Learn Atomic Representations.
CoRR, 2024

Projecting Molecules into Synthesizable Chemical Spaces.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Scientific discovery in the age of artificial intelligence.
Nat., 2023

2022
Reinforced Genetic Algorithm for Structure-based Drug Design.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sample Efficiency Matters: A Benchmark for Practical Molecular Optimization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Amortized Tree Generation for Bottom-up Synthesis Planning and Synthesizable Molecular Design.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Differentiable Scaffolding Tree for Molecule Optimization.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Pairwise Difference Regression: A Machine Learning Meta-algorithm for Improved Prediction and Uncertainty Quantification in Chemical Search.
J. Chem. Inf. Model., 2021

Differentiable Scaffolding Tree for Molecular Optimization.
CoRR, 2021

Therapeutics Data Commons: Machine Learning Datasets and Tasks for Therapeutics.
CoRR, 2021

Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

2020
Deep Learning in Protein Structural Modeling and Design.
Patterns, 2020

The Synthesizability of Molecules Proposed by Generative Models.
J. Chem. Inf. Model., 2020


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