公开(公告)号：US20240136028A1

公开(公告)日：2024-04-25

申请号：US18533469

申请日：2023-12-08

Applicant: Preferred Networks, Inc. ,  ENEOS Corporation

Inventor： Kosuke NAKAGO ,  Daisuke TANIWAKI ,  Motoki ABE ,  Marc Alan ONG ,  So TAKAMOTO ,  Takao KUDO ,  Yusuke ASANO

IPC: G16C20/70

CPC classification number: G16C20/70

Abstract: An information processing system includes a first information processing device and a second information processing device. The first information processing device is configured to receive the atomic information from the second information processing device, calculate a processing result corresponding to the atomic information by inputting the atomic information into a neural network, and transmit the processing result to the second information processing device. The second information processing device is configured to transmit atomic information to the first information processing device.

公开(公告)号：US20240211753A1

公开(公告)日：2024-06-27

申请号：US18425432

申请日：2024-01-29

Applicant: Preferred Networks, Inc. ,  Tokyo Electronic Limited

Inventor： Kosuke NAKAGO ,  Daisuke Motoki ,  Masaki Watanabe ,  Tomoki Komatsu ,  Hironori Moki ,  Masanobu Honda ,  Takahiko Kato ,  Tomohiko NIIZEKI

IPC: G06N3/08 ,  G06F18/214 ,  G06N3/04 ,  G06T7/00 ,  G06V10/32 ,  G06V10/764 ,  G06V10/82

CPC classification number: G06N3/08 ,  G06F18/214 ,  G06N3/04 ,  G06T7/0004 ,  G06V10/764 ,  G06V10/82 ,  G06T2207/20084 ,  G06T2207/30148 ,  G06V10/32

Abstract: With respect to a method performed by at least one processor, the method includes obtaining, by the at least one processor, data related to a first process for a first object, obtaining, by the at least one processor, non-processed object data of the first object, generating, by the at least one processor, first data including the data related to the first process for the first object and the non-processed object data of the first object, and adjusting a second process for a second object based on the first data.

公开(公告)号：US20200279148A1

公开(公告)日：2020-09-03

申请号：US16784717

申请日：2020-02-07

Applicant: Preferred Networks, Inc.

Inventor： Daisuke MOTOKI ,  Kosuke NAKAGO

IPC: G06N3/04 ,  G06N3/08

Abstract: A material structure analysis scheme for using machine learning to predict a general structure of an arbitrary material is provided. One aspect of the present disclosure relates to a material structure analysis method, including acquiring, by one or more processors, structural data representing a structure of a material and spectral data representing a spectrum of a material, inputting, by the one or more processors, the structural data to a first neural network to acquire a structural feature from the first neural network, inputting, by the one or more processors, the spectral data to a second neural network to acquire a spectral feature from the second neural network, and determining, by the one or more processors, a degree of coincidence between the material corresponding to the structural data and the material corresponding to the spectral data based on the structural feature and the spectral feature.

公开(公告)号：US20250014686A1

公开(公告)日：2025-01-09

申请号：US18896110

申请日：2024-09-25

Applicant: Preferred Networks, Inc.

Inventor： Kohei SHINOHARA ,  Kosuke NAKAGO ,  Akihide HAYASHI

IPC: G16C20/30 ,  G16C20/70

Abstract: An estimation apparatus according to an embodiment includes at least one memory and at least one processor. At least one processor described above inputs a feature amount of each of a plurality of atoms to a neural network to update the feature amount, and generates a parameter corresponding to each of the plurality of atoms based on the updated feature amount. At least one processor described above determines each of a plurality of charges corresponding to each of the plurality of atoms by using the parameter.

公开(公告)号：US20210209413A1

公开(公告)日：2021-07-08

申请号：US17189608

申请日：2021-03-02

Applicant: Preferred Networks, Inc ,  Tokyo Electron Limited

Inventor： Kosuke NAKAGO ,  Daisuke Motoki ,  Masaki Watanabe ,  Tomoki Komatsu ,  Hironori Moki ,  Masanobu Honda ,  Takahiko Kato ,  Tomohiko Niizeki

IPC: G06K9/62 ,  G06T7/00 ,  G06N3/04 ,  G06N3/08

Abstract: With respect to an inference method performed by at least one processor, the method includes inputting, by the at least one processor, into a learned model, non-processed object image data of a second object and data related to a second process for the second object, and inferring, by the at least one processor using the learned model, processed object image data of the second object on which the second process has been performed. The learned model has been trained so that an output obtained in response to non-processed object image data of a first object and data related to a first process for the first object being input approaches processed object image data of the first object on which the first process has been performed.

公开(公告)号：US20210183051A1

公开(公告)日：2021-06-17

申请号：US17189592

申请日：2021-03-02

Applicant: Preferred Networks, Inc.

Inventor： Kosuke NAKAGO ,  Daisuke MOTOKI ,  Masaki WATANABE ,  Tomoki KOMATSU

IPC: G06T7/00 ,  G06N3/08

Abstract: With respect to an inference method performed by at least one processor, the method includes inputting, by the at least one processor, into a learned model, second non-processed image data and second parameter data of a simulator, and inferring, by the at least one processor using the learned model, second processed image data. The learned model has been trained so that first processed image data, obtained as an output in response to first non-processed image data and first parameter data of the simulator for the first non-processed image data being input, approaches first simulator processed image data, obtained as a result of the simulator for the first non-processed image data by using the first parameter data.