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Cross-model format comparison

Grant US12596965B2 Kind: B2 Apr 07, 2026

Assignee

HiddenLayer, Inc.

Inventors

Kasimir Ralph Peter Schulz, David Beveridge

Abstract

A machine learning model representation is obtained from a model source and information characterizing the layers of the model representation is extracted to result in extracted model information. This extracted model information can be compared to information characterizing one or more known (i.e., previously characterized) machine learning models in order to determine whether there is a match based on layer information. A match can, in some cases, be used to determine an identity of the underlying machine learning model for the model representation. Information regarding the comparison (i.e., the model matching determination) can be provided to a consuming application or process. Related apparatus, systems, techniques and articles are also described.

CPC Classifications

G06N 20/20

Filing Date

2024-07-11

Application No.

18770545

Claims

25