Megan Stanley
Microsoft Research (United Kingdom)(GB)UK Health Security Agency(GB)
Publications by Year
Research Areas
Machine Learning in Materials Science, Computational Drug Discovery Methods, Scientific Computing and Data Management, Adversarial Robustness in Machine Learning, Explainable Artificial Intelligence (XAI)
Most-Cited Works
- → Fake it until you make it? Generative de novo design and virtual screening of synthesizable molecules(2023)41 cited
- → Re-evaluating retrosynthesis algorithms with Syntheseus(2024)28 cited
- → PREFER: A New Predictive Modeling Framework for Molecular Discovery(2023)16 cited
- → Shapley explainability on the data manifold(2020)12 cited
- FS-Mol: A Few-Shot Learning Dataset of Molecules(2021)
- Shapley-based explainability on the data manifold.(2020)
- → FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology(2024)8 cited
- STRUCTURAL MECHANICS AND MATERIALS(1977)