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Found 4 papers, 1 papers with code
Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations
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.
Optimizing Molecules using Efficient Queries from Property Evaluations
Machine learning based methods have shown potential for optimizing existing molecules with more desirable properties, a critical step towards accelerating new chemical discovery.
Combinatorial Black-Box Optimization with Expert Advice
We consider the problem of black-box function optimization over the boolean hypercube.
Nano-Material Configuration Design with Deep Surrogate Langevin Dynamics
We consider the problem of optimizing by sampling under multiple black-box constraints in nano-material design.
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