The Atomic Architects retweeted
🧵(1/6) We have updated the paper of EquiformerV2 to include more results. Currently, EquiformerV2 is the best model on the large-scale OC20 and OC22 datasets.
Joint work with @bwood_m, @abhshkdz from @OpenCatalyst and @tesssmidt.
Paper: arxiv.org/abs/2306.12059
Code: github.com/atomicarchitects/… and github.com/Open-Catalyst-Pro…
The Atomic Architects retweeted
Excited to share our latest survey paper: "Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems"! 🚀 ArXiv: arxiv.org/abs/2307.08423.
The Atomic Architects retweeted
🧵(1/6) We propose EquiformerV2 with state-of-the-art results on all OC20 tasks and AdsorbML.
Joint work with @bwood_m , @abhshkdz from @OpenCatalyst and @tesssmidt .
Besides, thank @_akhaliq for tweeting before.
Paper: arxiv.org/abs/2306.12059
Code: github.com/atomicarchitects/…
The Atomic Architects retweeted
Equiformer Paper: openreview.net/forum?id=KwmP…
Equiformer Code: github.com/atomicarchitects/…
(3/3)
The Atomic Architects retweeted
In Equiformer, we've replaced Transformer operations with equivariant versions including equivariant attention. Equiformer achieves competitive results on QM9, MD17 and OC20 datasets, demonstrating that Transformers can be effective models for 3D atomistic graphs! (2/3)
The Atomic Architects retweeted
Our work "Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs" has been accepted as a spotlight @ #ICLR2023! A big congrats to @yilunliao whose determination and skill made this possible! (1/3)
Congrats to @yilunliao on winning 2nd place in the Open Catalysis Challenge at NeurIPS 2022! opencatalystproject.org/chal…






