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Materials Science

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SigOpt Summit 2021

Multi-fidelity prediction of molecular optical peaks with deep learning

Deep learning to design nuclear-targeting abiotic miniproteins

Sampling Lattices in Semi-Grand Canonical Ensemble with Autoregressive Machine Learning

Highlight: Beyond the Pareto Efficient Frontier: Constraint Active Search for Multiobjective Experimental Design, ICML 2021

Chemistry-informed Macromolecule Graph Representation for Similarity Computation and Supervised Learning

GEOM: Energy-annotated molecular conformations for property prediction and molecular generation

Reducing Reflection in Additive Manufacturing of Optoelectronics

Creating glasswing butterfly-inspired durable antifogging superomniphobic supertransmissive, superclear nanostructured glass through Bayesian learning and optimization

New superomniphobic glass soars high on butterfly wings using machine learning

Creating glasswing butterfly-inspired durable antifogging superomniphobic supertransmissive, superclear nanostructured glass through Bayesian learning and optimization

A Self-Healing Glass, Inspired by a Butterfly Wing

Nanostructured Glass Is Based on Butterfly Wing

New superomniphobic glass soars high on butterfly wings using machine learning

Practical Complications in Applying Bayesian Optimization to Understand Tradeoffs between Substrate Fabrication Processes

Using Bayesian Optimization to Improve Solar Panel Performance by Developing Antireflective, Superomniphobic Glass