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06/07/2021
Equivariant Graph Neural Networks for 3D Macromolecular Structure
Representing and reasoning about 3D structures of macromolecules is emer...
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05/16/2021
Protein sequence-to-structure learning: Is this the end(-to-end revolution)?
The potential of deep learning has been recognized in the protein struct...
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12/07/2020
ATOM3D: Tasks On Molecules in Three Dimensions
Computational methods that operate directly on three-dimensional molecul...
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11/27/2020
Protein model quality assessment using rotation-equivariant, hierarchical neural networks
Proteins are miniature machines whose function depends on their three-di...
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09/03/2020
Learning from Protein Structure with Geometric Vector Perceptrons
Learning on 3D structures of large biomolecules is emerging as a distinc...
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06/25/2020
Geometric Prediction: Moving Beyond Scalars
Many quantities we are interested in predicting are geometric tensors; w...
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06/04/2019
Learning Neural PDE Solvers with Convergence Guarantees
Partial differential equations (PDEs) are widely used across the physica...
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12/10/2017