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Lucky number 7. Our latest preprint ended up with a fun number on arXiv: arxiv.org/abs/2007.07070

📣 Don't miss this!!! Our third annual Berkeley Lab Research SLAM will be streamed LIVE this Thursday, Sept., 17 at 3p PT. YOU (our virtual audience) will be given the opportunity to select the "People's Choice Award!" More » slam.lbl.gov #LabSLAM2020 LBNL Career Pathways

Woohoo! Go Revathi Jambunathan!!! Can't wait to see you representing the Computing Sciences Area in the #LabSLAM2020.

Best of luck to all finalists! Can't wait to see you all SLAM'n! #LabSLAM2020

400 people tuned into the #LabSLAM2020. Good luck to all the finalists! LBNL Career Pathways

"Imagine loosing your GPS signal... in the space..." Revathi Jambunathan Revathi from Berkeley Lab Computing Sciences Area on her super-computer research on pulsars. #LabSLAM2020 Berkeley Lab LBNL Career Pathways

Congrats to Revathi Jambunathan on winning 1st place at the #LabSLAM2020!!!

During this National Postdoc Appreciation Week #NPAW I want to shine a light on my incredibly talented and awesome postdocs Prof. Tess Smidt, Yu-Hang Tang, Mekena, @muammar, Miro Urbanek, lindsaybassman Thom Popovici and Katie Klymko pushing the scientific frontiers Berkeley Lab Computing Sciences Area.

Wohoo - PauliNet, our deep #NeuralNetwork solution of the electronic Schrödinger equation is out in Nature Chemistry. Huge respect for @jhrmnn and Zeno Schätzle for championing this. Deep Quantum Monte Carlo is the future! nature.com/articles/s4155…

Attention all soon to graduate computational PhD students and early postdocs! Apply to become an Alvarez Fellow at Berkeley Lab! It's a fantastic opportunity to grow your independent research ideas amidst the diverse expertise and interdisciplinary culture of Berkeley Lab.

Prediction of tunable spin-orbit gapped materials for dark matter detection, Katherine Inzani, Alireza Faghaninia, and Sinéad M. Griffin (Sinéad Griffin) Molecular Foundry Berkeley Lab #materials #darkmatter go.aps.org/3o8e5ua

Excited to see our work on using Euclidean neural networks to find symmetry-implied missing data in Physical Review Research! (Better to tweet late than never?)

We had a special guest in our journal club today! Prof. Tess Smidt gave a great talk on Equivariant Networks. #DeepLearning

Congrats to Yi-Lun Liao on winning 2nd place in the Open Catalysis Challenge at NeurIPS 2022! opencatalystproject.org/challenge.html

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)

Equiformer Paper: openreview.net/forum?id=KwmPf… Equiformer Code: github.com/atomicarchitec… (3/3)

🧵(1/6) We propose EquiformerV2 with state-of-the-art results on all OC20 tasks and AdsorbML. Joint work with Brandon Wood , Abhishek Das from FAIR Chemistry and Prof. Tess Smidt . Besides, thank AK for tweeting before. Paper: arxiv.org/abs/2306.12059 Code: github.com/atomicarchitec…

Excited to share our latest survey paper: "Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems"! 🚀 ArXiv: arxiv.org/abs/2307.08423.

🧵(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 Brandon Wood, Abhishek Das from FAIR Chemistry and Prof. Tess Smidt. Paper: arxiv.org/abs/2306.12059 Code: