Techniques for compositional protein generation
AssigneeNVIDIA Corporation
InventorsKarsten KREIS, Tomas GEFFNER, Bowen JING, Hannes Axel STAERK, Arash VAHDAT
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Abstract
The disclosed method for generating proteins includes generating, using a trained machine learning model, a first protein based on a three-dimensional (3D) representation of a spatial layout for the first protein, where generating the first protein comprises applying cross-attention between one or more first tokens associated with the 3D representation and one or more second tokens associated with a second protein.
Claims20
A computer-implemented method for generating proteins, the method comprising:
- generating, using a trained machine learning model, a first protein based on a three-dimensional (3D) representation of a spatial layout for the first protein,
- wherein generating the first protein comprises applying cross-attention between one or more first tokens associated with the 3D representation and one or more second tokens associated with a second protein.
One or more non-transitory computer-readable media storing instructions that, when executed by at least one processor, cause the at least one processor to perform the steps of:
- generating, using a trained machine learning model, a first protein based on a three-dimensional (3D) representation of a spatial layout for the first protein,
- wherein generating the first protein comprises applying cross-attention between one or more first tokens associated with the 3D representation and one or more second tokens associated with a second protein.
A system, comprising:
- one or more memories storing instructions;
- and
- one or more processors that are coupled to the one or more memories and, when executing the instructions, are configured to:
- generate, using a trained machine learning model, a first protein based on a three-dimensional (3D) representation of a spatial layout for the first protein,
- wherein generating the first protein comprises applying cross-attention between one or more first tokens associated with the 3D representation and one or more second tokens associated with a second protein.
Dependencies are inferred from the claim text.