Showing 1–14 of 14 results
/ Date/ Name
Jul 8, 2022Accelerating Material Design with the Generative Toolkit for Scientific DiscoveryFeb 1, 2022An Empirical Study of Modular Bias Mitigators and EnsemblesSep 24, 2021AI Explainability 360: Impact and DesignOct 11, 2022Navigating Ensemble Configurations for Algorithmic FairnessMay 24, 2018Fairness GANApr 4, 2024GP-MoLFormer: A Foundation Model For Molecular GenerationOct 3, 2018AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic BiasDec 2, 2021Sample-Efficient Generation of Novel Photo-acid Generator Molecules using a Deep Generative ModelJun 5, 2025GP-MoLFormer-Sim: Test Time Molecular Optimization through Contextual Similarity GuidanceSep 6, 2019One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability TechniquesApr 2, 2020CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative ModelsApr 19, 2022Accelerating Inhibitor Discovery With A Deep Generative Foundation Model: Validation for SARS-CoV-2 Drug TargetsFeb 17, 2023Function Composition in Trustworthy Machine Learning: Implementation Choices, Insights, and QuestionsJul 14, 2022Attribute Graphs Underlying Molecular Generative Models: Path to Learning with Limited Data