1 citations · 2 across the 4 of their papers we have counts for
4 papers
Autonomous epitaxial atomic-layer synthesis via real-time computer vision of electron diffraction
Haotong Liang, Yunlong Sun, Ryan Paxson +8
Autonomous science platforms which make decisions on the fly are fundamentally changing the outlook for materials development. AI-driven schemes can effectively reduce the total nu…
Quantum Kernel Machine Learning for Autonomous Materials Science
Felix Adams, Daiwei Zhu, David W. Steuerman +2
Autonomous materials science, where active learning is used to navigate large compositional phase space, has emerged as a powerful vehicle to rapidly explore new materials. A cruci…
Conditional Latent Space Molecular Scaffold Optimization for Accelerated Molecular Design
Onur Boyar, Hiroyuki Hanada, Ichiro Takeuchi
The rapid discovery of new chemical compounds is essential for advancing global health and developing treatments. While generative models show promise in creating novel molecules,…
Crystal-LSBO: Automated Design of De Novo Crystals with Latent Space Bayesian Optimization
Onur Boyar, Yanheng Gu, Yuji Tanaka +3
Generative modeling of crystal structures is significantly challenged by the complexity of input data, which constrains the ability of these models to explore and discover novel cr…