公开(公告)号：US20230109729A1

公开(公告)日：2023-04-13

申请号：US17958597

申请日：2022-10-03

Applicant: NEC Laboratories America, Inc.

Inventor： Yuncong Chen ,  Zhengzhang Chen ,  Xuchao Zhang ,  Wenchao Yu ,  Haifeng Chen ,  LuAn Tang ,  Zexue He

IPC: G06N3/08 ,  G06F40/47 ,  G06F40/30

Abstract: A computer-implemented method for multi-model representation learning is provided. The method includes encoding, by a trained time series (TS) encoder, an input TS segment into a TS-shared latent representation and a TS-private latent representation. The method further includes generating, by a trained text generator, a natural language text that explains the input TS segment, responsive to the TS-shared latent representation, the TS-private latent representation, and a text-private latent representation.

公开(公告)号：US12205028B2

公开(公告)日：2025-01-21

申请号：US17958597

申请日：2022-10-03

Applicant: NEC Laboratories America, Inc.

Inventor： Yuncong Chen ,  Zhengzhang Chen ,  Xuchao Zhang ,  Wenchao Yu ,  Haifeng Chen ,  LuAn Tang ,  Zexue He

IPC: G06F40/30 ,  G06F40/47 ,  G06N3/08

Abstract: A computer-implemented method for multi-model representation learning is provided. The method includes encoding, by a trained time series (TS) encoder, an input TS segment into a TS-shared latent representation and a TS-private latent representation. The method further includes generating, by a trained text generator, a natural language text that explains the input TS segment, responsive to the TS-shared latent representation, the TS-private latent representation, and a text-private latent representation.