1 code implementation • 6 Jun 2021 • Victor Fung, Jiaxin Zhang, Guoxiang Hu, P. Ganesh, Bobby G. Sumpter
The ability to readily design novel materials with chosen functional properties on-demand represents a next frontier in materials discovery.
1 code implementation • 2 Dec 2022 • Jiaxin Zhang, Sirui Bi, Victor Fung
In the scope of "AI for Science", solving inverse problems is a longstanding challenge in materials and drug discovery, where the goal is to determine the hidden structures given a set of desirable properties.
1 code implementation • 27 Jul 2022 • Victor Fung, Shuyi Jia, Jiaxin Zhang, Sirui Bi, Junqi Yin, P. Ganesh
These methods would help identify or, in the case of generative models, even create novel crystal structures of materials with a set of specified functional properties to then be synthesized or isolated in the laboratory.
1 code implementation • 12 Oct 2023 • Deyu Zou, Shikun Liu, Siqi Miao, Victor Fung, Shiyu Chang, Pan Li
Geometric deep learning (GDL) has gained significant attention in various scientific fields, chiefly for its proficiency in modeling data with intricate geometric structures.
no code implementations • 16 Nov 2023 • Sirui Bi, Victor Fung, Jiaxin Zhang
This, in turn, facilitates a probabilistic interpretation of observational data for decision-making.