EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

1 code implementation • 21 Jun 2023 • Yi-Lun Liao, Brandon Wood, Abhishek Das, Tess Smidt

Equivariant Transformers such as Equiformer have demonstrated the efficacy of applying Transformers to the domain of 3D atomistic systems.

Spherical Channels for Modeling Atomic Interactions

1 code implementation • 29 Jun 2022 • C. Lawrence Zitnick, Abhishek Das, Adeesh Kolluru, Janice Lan, Muhammed Shuaibi, Anuroop Sriram, Zachary Ulissi, Brandon Wood

We propose the Spherical Channel Network (SCN) to model atomic energies and forces.

The Open Catalyst 2020 (OC20) Dataset and Community Challenges

4 code implementations • 20 Oct 2020 • Lowik Chanussot, Abhishek Das, Siddharth Goyal, Thibaut Lavril, Muhammed Shuaibi, Morgane Riviere, Kevin Tran, Javier Heras-Domingo, Caleb Ho, Weihua Hu, Aini Palizhati, Anuroop Sriram, Brandon Wood, Junwoong Yoon, Devi Parikh, C. Lawrence Zitnick, Zachary Ulissi

Catalyst discovery and optimization is key to solving many societal and energy challenges including solar fuels synthesis, long-term energy storage, and renewable fertilizer production.

An Introduction to Electrocatalyst Design using Machine Learning for Renewable Energy Storage

no code implementations • 14 Oct 2020 • C. Lawrence Zitnick, Lowik Chanussot, Abhishek Das, Siddharth Goyal, Javier Heras-Domingo, Caleb Ho, Weihua Hu, Thibaut Lavril, Aini Palizhati, Morgane Riviere, Muhammed Shuaibi, Anuroop Sriram, Kevin Tran, Brandon Wood, Junwoong Yoon, Devi Parikh, Zachary Ulissi

As we increase our reliance on renewable energy sources such as wind and solar, which produce intermittent power, storage is needed to transfer power from times of peak generation to peak demand.

BIG-bench Machine Learning