ASK-Berkeley
Research group at UC Berkeley, working on machine learning methods for the physical sciences.
Popular repositories Loading
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Neural-Spectral-Methods
Neural-Spectral-Methods Public[ICLR 2024] Neural Spectral Methods: Self-supervised learning in the spectral domain.
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physics-NNs-hard-constraints
physics-NNs-hard-constraints Public[ICLR 2024] Scaling physics-informed hard constraints with mixture-of-experts.
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BADGER-SBDD
BADGER-SBDD PublicOfficial code base for "General Binding Affinity Guidance for Diffusion Models in Structure-Based Drug Design"
Repositories
Showing 7 of 7 repositories
- CoarsenConf Public
ASK-Berkeley/CoarsenConf’s past year of commit activity - physics-NNs-hard-constraints Public
[ICLR 2024] Scaling physics-informed hard constraints with mixture-of-experts.
ASK-Berkeley/physics-NNs-hard-constraints’s past year of commit activity - BADGER-SBDD Public
Official code base for "General Binding Affinity Guidance for Diffusion Models in Structure-Based Drug Design"
ASK-Berkeley/BADGER-SBDD’s past year of commit activity - Neural-Spectral-Methods Public
[ICLR 2024] Neural Spectral Methods: Self-supervised learning in the spectral domain.
ASK-Berkeley/Neural-Spectral-Methods’s past year of commit activity