Search Results for author: Samuel Hoffman

Found 4 papers, 1 papers with code

Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations

no code implementations8 Jun 2021 Yair Schiff, Vijil Chenthamarakshan, Samuel Hoffman, Karthikeyan Natesan Ramamurthy, Payel Das

Deep generative models have emerged as a powerful tool for learning useful molecular representations and designing novel molecules with desired properties, with applications in drug discovery and material design.

Drug Discovery Topological Data Analysis

Optimizing Molecules using Efficient Queries from Property Evaluations

1 code implementation3 Nov 2020 Samuel Hoffman, Vijil Chenthamarakshan, Kahini Wadhawan, Pin-Yu Chen, Payel Das

Machine learning based methods have shown potential for optimizing existing molecules with more desirable properties, a critical step towards accelerating new chemical discovery.

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