2 citations · 3 across the 2 of their papers we have counts for
2 papers
physics.comp-ph2024★ 1 cited
On the Robustness of Machine Learning Models in Predicting Thermodynamic Properties: a Case of Searching for New Quasicrystal Approximants
Fedor S. Avilov, Roman A. Eremin, Semen A. Budennyy +1
Despite an artificial intelligence-assisted modeling of disordered crystals is a widely used and well-tried method of new materials design, the issues of its robustness, reliabilit…
cond-mat.mtrl-sci2024★ 2 cited
Unleashing the power of novel conditional generative approaches for new materials discovery
Lev Novitskiy, Vladimir Lazarev, Mikhail Tiutiulnikov +6
For a very long time, computational approaches to the design of new materials have relied on an iterative process of finding a candidate material and modeling its properties. AI ha…