The Open Molecules 2025 dataset is out! With >100M gold-standard ωB97M-V/def2-TZVPD calcs of biomolecules, electrolytes, metal complexes, and small molecules, OMol is by far the largest, most diverse, and highest quality molecular DFT dataset for training MLIPs ever made 1/N
For existing MLIPs, lower test errors do not always translate to better performance in downstream tasks. We bridge this gap by proposing eSEN -- SOTA performance on compliant Matbench-Discovery (F1 0.831, κSRME 0.321) and phonon prediction.
arxiv.org/abs/2502.12147
1/6
I’m excited to share our latest work on generative models for materials called FlowLLM.
FlowLLM combines Large Language Models and Riemannian Flow Matching in a simple, yet surprisingly effective way for generating materials.
arxiv.org/abs/2410.23405@bkmi13@RickyTQChen@bwood_m
Our team at FAIR is looking for research interns in 2025. We work on a range of AI for chemistry topics from applied projects to machine learning potentials and generative models.
If you are interested please apply and don’t hesitate to reach out!
metacareers.com/jobs/124365935…
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