公开(公告)号：US20240220856A1

公开(公告)日：2024-07-04

申请号：US18150135

申请日：2023-01-04

Applicant: AUTODESK, INC.

Inventor： Andre Maurice SCHREIBER ,  Ran ZHANG

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: One embodiment of the present invention sets forth a technique for training machine learning models to generate embeddings for different shapes. The technique includes executing two or more machine learning models to generate embeddings from shapes associated with multiple formats. The technique also includes computing a first plurality of similarities between positive pairs of embeddings that include two different embeddings for the same shape, and computing a second plurality of similarities between negative pairs of embeddings that include embeddings for different shapes. The technique further includes training the machine learning models based on the computed similarities.

公开(公告)号：US20240220532A1

公开(公告)日：2024-07-04

申请号：US18150129

申请日：2023-01-04

Applicant: AUTODESK, INC.

Inventor： Andre Maurice SCHREIBER ,  Ran ZHANG

IPC: G06F16/532 ,  G06F16/54

CPC classification number: G06F16/532 ,  G06F16/54

Abstract: One embodiment of the present invention sets forth a technique for analyzing similarities associated with a plurality of shapes. The technique includes determining a first embedding for a first query shape associated with a first format and a first plurality of embeddings for a first plurality of shapes associated with a second format, wherein the first embedding and the first plurality of embeddings are generated by one or more trained machine learning models based on the first query shape and the first plurality of shapes. The technique also includes matching, based on the first embedding and the first plurality of embeddings, the first query shape to one or more shapes included in the first plurality of shapes. The technique further includes outputting the one or more shapes in a first response associated with the first query shape.