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Found 5 papers, 3 papers with code
Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching
We introduce Adjoint Sampling, a highly scalable and efficient algorithm for learning diffusion processes that sample from unnormalized densities, or energy functions.
EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
Equivariant Transformers such as Equiformer have demonstrated the efficacy of applying Transformers to the domain of 3D atomistic systems.
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Spherical Channels for Modeling Atomic Interactions
We propose the Spherical Channel Network (SCN) to model atomic energies and forces.
The Open Catalyst 2020 (OC20) Dataset and Community Challenges
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
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.
