The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jul. 28, 2026

Filed:

Aug. 30, 2023
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Igor Melnyk, White Plains, NY (US);

Aurelie Chloe Lozano, Scarsdale, NY (US);

Payel Das, New York, NY (US);

Enara C. Vijil, Millwood, NY (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G16B 15/20 (2019.01); G06N 20/00 (2019.01); G16B 15/30 (2019.01); G16B 40/20 (2019.01);
U.S. Cl.
CPC ...
G16B 15/20 (2019.02); G06N 20/00 (2019.01); G16B 15/30 (2019.02); G16B 40/20 (2019.02);
Abstract

A distilled machine learning model is produced via initializing a first model with initial weights. An input protein sequence is input into both the first model and a folding protein model, wherein the inputting to the first model generates logits, and wherein the inputting to the folding protein model generates one or more predictive metrics. The one or more predictive metrics are discretized into classes and a first cross-entropy loss is computed based on the logits and the classes. The first model is optimized based on the first cross-entropy loss so that the optimized first model is the distilled machine learning model and an additional machine learning model is trained, using the distilled machine learning model, to perform a downstream protein modeling task.


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