Muhammed Shuaibi
@mshuaibii
Research Engineer at FAIR, @AIatMeta @OpenCatalyst
ID: 1301888801715957760
https://mshuaibii.github.io/ 04-09-2020 14:24:21
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320 Followers
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CrystalLLM is up on arxiv! In the paper, we show that LLMs can be fine-tuned to produce 3D structures that are stable according to density functional theory (DFT). arxiv.org/abs/2402.04379 w/ Anuroop Sriram, Andrea Madotto, Andrew Gordon Wilson, Zack Ulissi 1/6
🧵(1/7) Excited to share that our work, EquiformerV2, has been accepted to #ICLR2024. EquiformerV2 is the state-of-the-art on large-scale atomistic benchmarks -- OC20, OC22, AdsorbML, and ODAC23. Joint work with Brandon Wood, Abhishek Das from FAIR Chemistry and Prof. Tess Smidt Paper:
Paper shared on arXiv showing catalyst AI/ML models trained on datasets like FAIR Chemistry can generalize to solid solutions like high entropy alloys (HEA)! This is exciting because the design space of HEAs (with >5 components) is combinatorially large. arxiv.org/abs/2403.09811
🧵(1/9) Introducing DeNS, an auxiliary training objective that generalizes denoising to non-equilibrium atomistic structures, improving the performance of equivariant force fields such as Equiformer. Joint work with Prof. Tess Smidt and Abhishek Das from FAIR Chemistry Preprint:
Announcing our new model for materials! FlowMM... - Generates stable & novel materials efficiently - Predicts crystal structure accurately - Generalizes Riemannian Flow Matching to point clouds w/ periodic boundaries arxiv.org/abs/2406.04713 Ricky T. Q. Chen Anuroop Sriram Brandon Wood
A few of us will be at the AC conference this week. We will be sharing some of our ongoing computational-experimental efforts for electrocatalysis. Make sure to come and chat with Jehad Abed, Muhammed Shuaibi, and Larry Zitnick.