1 citations · 1 across the 4 of their papers we have counts for
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Self-Conditioned Denoising for Atomistic Representation Learning
Tynan Perez, Rafael Gomez-Bombarelli
The success of large-scale pretraining in NLP and computer vision has catalyzed growing efforts to develop analogous foundation models for the physical sciences. However, pretraini…
Zatom-1: Towards a Multimodal Foundation Model for 3D Molecules and Materials
Alex Morehead, Miruna Cretu, Antonia Panescu +14
General-purpose 3D modeling in chemistry encompasses molecules and materials, requiring both generative and predictive capabilities. However, most existing AI approaches are optimi…
Known Unknowns: Out-of-Distribution Property Prediction in Materials and Molecules
Nofit Segal, Aviv Netanyahu, Kevin P. Greenman +2
Discovery of high-performance materials and molecules requires identifying extremes with property values that fall outside the known distribution. Therefore, the ability to extrapo…