activity
20062023
most citedOn-the-fly Closed-loop Autonomous Materials Discovery via Bayesian Active Learning

549 citations · 3.1k across the 55 of their papers we have counts for

collaborators
Showing 2019Show all

5 papers · 1 filter

cond-mat.supr-con2019★ 26 cited

Recent advances in high-throughput superconductivity research

J. Yuan, V. Stanev, C. Gao +2

Superconducting materials find applications in a rapidly growing number of technological areas, and searching for novel superconductors continues to be a major scientific task. How…

cond-mat.mtrl-sci2019★ 444 cited

Fatigue-resistant high-performance elastocaloric materials via additive manufacturing

Huilong Hou, Emrah Simsek, Tao Ma +15

Elastocaloric cooling, which exploits the latent heat released and absorbed as stress-induced phase transformations are reversibly cycled in shape memory alloys, has recently emerg…

cond-mat.supr-con2019★ 5 cited

Microwave Meissner Screening of Proximity coupled Topological Insulator / Superconductor Bilayers

Seokjin Bae, Seunghun Lee, Xiaohang Zhang +2

The proximity coupled topological insulator / superconductor (TI/SC) bilayer system is a representative system to realize topological superconductivity. In order to better understa…

stat.ML2019

Active learning for enumerating local minima based on Gaussian process derivatives

Yu Inatsu, Daisuke Sugita, Kazuaki Toyoura +1

We study active learning (AL) based on Gaussian Processes (GPs) for efficiently enumerating all of the local minimum solutions of a black-box function. This problem is challenging…

cond-mat.mtrl-sci2019★ 1 cited

Materials development by interpretable machine learning

Yuma Iwasaki, Ryoto Sawada, Valentin Stanev +7

Machine learning technologies are expected to be great tools for scientific discoveries. In particular, materials development (which has brought a lot of innovation by finding new…