🔥The 9th Round of Easy Loan, Earn $40 Reward is in progress❗️ ⏰ Promotion Period: January 15th - Feburary 15th, 2025 👉 Register now and check more details at gate.io/campaigns/358

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:

Newly published today in ACS Central Science — Meta and Georgia Tech researchers released a dataset + SOTA AI models to help accelerate research on Direct Air Capture — a key technology to combat climate change ➡️ go.fb.me/eojy3k

Introducing fairchem - our revamped codebase consolidating our AI modeling efforts in chemistry and materials science. fairchem makes it easy to interface with our data, models, demos, and applications - including an easy to use ASE calculator: github.com/FAIR-Chem/fair…

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

Introducing Meta’s Open Materials 2024 (OMat24) Dataset and Models! All under permissive open licenses for commercial and non-commercial use! Paper: arxiv.org/abs/2410.12771 Dataset: huggingface.co/datasets/fairc… Models: huggingface.co/fairchem/OMAT24 🧵1/x

Excited to unveil OCx24, a two-year effort with University of Toronto and @VSParticle! We've synthesized and tested in the lab hundreds of metal alloys for catalysis. With 685 million AI-accelerated simulations, we analyzed 20,000 materials to try and bridge simulation and reality. Paper:

Introducing All-atom Diffusion Transformers — towards Foundation Models for generative chemistry, from my internship with the FAIR Chemistry team FAIR Chemistry AI at Meta There are a couple ML ideas which I think are new and exciting in here 👇

Exciting new step toward foundational generative models for Chemistry! Training a unified model for molecules & materials has been a challenge—until now. Our new work uses Latent Diffusion to jointly model both, paving the way for more modalities in the future! Led by Chaitanya K. Joshi.

We are presenting 3 orals and 1 spotlight at #ICLR2025 on two primary topics: On generalizing the data-driven flow matching algorithm to jump processes, arbitrary discrete corruption processes, and beyond. And on highly scalable algorithms for reward-driven learning settings.