JP7655512B2 - 情報処理装置、学習済みモデル生成装置、情報処理方法、学習済みモデル生成方法、情報処理プログラム、及び学習済みモデル生成プログラム - Google Patents
情報処理装置、学習済みモデル生成装置、情報処理方法、学習済みモデル生成方法、情報処理プログラム、及び学習済みモデル生成プログラム Download PDFInfo
- Publication number
- JP7655512B2 JP7655512B2 JP2023130520A JP2023130520A JP7655512B2 JP 7655512 B2 JP7655512 B2 JP 7655512B2 JP 2023130520 A JP2023130520 A JP 2023130520A JP 2023130520 A JP2023130520 A JP 2023130520A JP 7655512 B2 JP7655512 B2 JP 7655512B2
- Authority
- JP
- Japan
- Prior art keywords
- crystal
- substance
- trained
- data
- training
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
- G06N3/0455—Auto-encoder networks; Encoder-decoder networks
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/044—Recurrent networks, e.g. Hopfield networks
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/044—Recurrent networks, e.g. Hopfield networks
- G06N3/0442—Recurrent networks, e.g. Hopfield networks characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU]
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/0464—Convolutional networks [CNN, ConvNet]
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/047—Probabilistic or stochastic networks
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/0475—Generative networks
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/048—Activation functions
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/084—Backpropagation, e.g. using gradient descent
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/088—Non-supervised learning, e.g. competitive learning
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/0895—Weakly supervised learning, e.g. semi-supervised or self-supervised learning
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/09—Supervised learning
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/094—Adversarial learning
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/096—Transfer learning
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/0985—Hyperparameter optimisation; Meta-learning; Learning-to-learn
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
- G16C20/70—Machine learning, data mining or chemometrics
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
- G16C20/30—Prediction of properties of chemical compounds, compositions or mixtures
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- G16C60/00—Computational materials science, i.e. ICT specially adapted for investigating the physical or chemical properties of materials or phenomena associated with their design, synthesis, processing, characterisation or utilisation
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Software Systems (AREA)
- Artificial Intelligence (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Computation (AREA)
- Computing Systems (AREA)
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- General Health & Medical Sciences (AREA)
- Mathematical Physics (AREA)
- General Engineering & Computer Science (AREA)
- Biophysics (AREA)
- Molecular Biology (AREA)
- Computational Linguistics (AREA)
- Biomedical Technology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Medical Informatics (AREA)
- Probability & Statistics with Applications (AREA)
- Databases & Information Systems (AREA)
- Chemical & Material Sciences (AREA)
- Crystallography & Structural Chemistry (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Analysing Materials By The Use Of Radiation (AREA)
Priority Applications (5)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2023130520A JP7655512B2 (ja) | 2022-11-21 | 2023-08-09 | 情報処理装置、学習済みモデル生成装置、情報処理方法、学習済みモデル生成方法、情報処理プログラム、及び学習済みモデル生成プログラム |
| CN202380078286.2A CN120188167A (zh) | 2022-11-21 | 2023-11-14 | 信息处理装置、已学习模型生成装置、信息处理方法、已学习模型生成方法、信息处理程序和已学习模型生成程序 |
| PCT/JP2023/040970 WO2024111471A1 (ja) | 2022-11-21 | 2023-11-14 | 情報処理装置、学習済みモデル生成装置、情報処理方法、学習済みモデル生成方法、情報処理プログラム、及び学習済みモデル生成プログラム |
| EP23894480.5A EP4625255A1 (en) | 2022-11-21 | 2023-11-14 | Information processing device, trained model generation device, information processing method, trained model generation method, information processing program, and trained model generation program |
| JP2025039567A JP2025090756A (ja) | 2022-11-21 | 2025-03-12 | 情報処理装置、学習済みモデル生成装置、情報処理方法、学習済みモデル生成方法、情報処理プログラム、及び学習済みモデル生成プログラム |
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2022186043 | 2022-11-21 | ||
| JP2022186043 | 2022-11-21 | ||
| JP2023130520A JP7655512B2 (ja) | 2022-11-21 | 2023-08-09 | 情報処理装置、学習済みモデル生成装置、情報処理方法、学習済みモデル生成方法、情報処理プログラム、及び学習済みモデル生成プログラム |
Related Child Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2025039567A Division JP2025090756A (ja) | 2022-11-21 | 2025-03-12 | 情報処理装置、学習済みモデル生成装置、情報処理方法、学習済みモデル生成方法、情報処理プログラム、及び学習済みモデル生成プログラム |
Publications (3)
| Publication Number | Publication Date |
|---|---|
| JP2024074765A JP2024074765A (ja) | 2024-05-31 |
| JP2024074765A5 JP2024074765A5 (https=) | 2024-12-10 |
| JP7655512B2 true JP7655512B2 (ja) | 2025-04-02 |
Family
ID=91195613
Family Applications (2)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2023130520A Active JP7655512B2 (ja) | 2022-11-21 | 2023-08-09 | 情報処理装置、学習済みモデル生成装置、情報処理方法、学習済みモデル生成方法、情報処理プログラム、及び学習済みモデル生成プログラム |
| JP2025039567A Pending JP2025090756A (ja) | 2022-11-21 | 2025-03-12 | 情報処理装置、学習済みモデル生成装置、情報処理方法、学習済みモデル生成方法、情報処理プログラム、及び学習済みモデル生成プログラム |
Family Applications After (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2025039567A Pending JP2025090756A (ja) | 2022-11-21 | 2025-03-12 | 情報処理装置、学習済みモデル生成装置、情報処理方法、学習済みモデル生成方法、情報処理プログラム、及び学習済みモデル生成プログラム |
Country Status (4)
| Country | Link |
|---|---|
| EP (1) | EP4625255A1 (https=) |
| JP (2) | JP7655512B2 (https=) |
| CN (1) | CN120188167A (https=) |
| WO (1) | WO2024111471A1 (https=) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118820284B (zh) * | 2024-09-13 | 2024-12-27 | 清华大学深圳国际研究生院 | 一种基于语义理解的晶体材料结构生成方法、计算机可读存储介质及计算机程序产品 |
| CN120912692B (zh) * | 2025-09-29 | 2026-01-20 | 山东华云三维科技有限公司 | 一种面向增材制造的晶格数据压缩方法、系统及介质 |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2018010428A (ja) | 2016-07-12 | 2018-01-18 | 株式会社日立製作所 | 材料創成装置、および材料創成方法 |
| JP2020166706A (ja) | 2019-03-29 | 2020-10-08 | 株式会社クロスアビリティ | 結晶形予測装置、結晶形予測方法、ニューラルネットワークの製造方法、及びプログラム |
| WO2021262792A1 (en) | 2020-06-24 | 2021-12-30 | Sri International | Unsupervised invertible physics-based vector representation for molecules |
| WO2023047843A1 (ja) | 2021-09-27 | 2023-03-30 | オムロン株式会社 | モデル生成方法、データ提示方法、データ生成方法、推定方法、モデル生成装置、データ提示装置、データ生成装置、及び推定装置 |
| CN116343937A (zh) | 2022-12-28 | 2023-06-27 | 深圳晶泰科技有限公司 | 晶体结构生成方法、装置、电子设备及计算机可读存储介质 |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP7319902B2 (ja) | 2019-12-12 | 2023-08-02 | 株式会社ニチベイ | 縦型ブラインド |
| JP7673896B2 (ja) | 2021-06-04 | 2025-05-09 | ダイハツ工業株式会社 | 車両構造 |
-
2023
- 2023-08-09 JP JP2023130520A patent/JP7655512B2/ja active Active
- 2023-11-14 CN CN202380078286.2A patent/CN120188167A/zh active Pending
- 2023-11-14 EP EP23894480.5A patent/EP4625255A1/en active Pending
- 2023-11-14 WO PCT/JP2023/040970 patent/WO2024111471A1/ja not_active Ceased
-
2025
- 2025-03-12 JP JP2025039567A patent/JP2025090756A/ja active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2018010428A (ja) | 2016-07-12 | 2018-01-18 | 株式会社日立製作所 | 材料創成装置、および材料創成方法 |
| JP2020166706A (ja) | 2019-03-29 | 2020-10-08 | 株式会社クロスアビリティ | 結晶形予測装置、結晶形予測方法、ニューラルネットワークの製造方法、及びプログラム |
| WO2021262792A1 (en) | 2020-06-24 | 2021-12-30 | Sri International | Unsupervised invertible physics-based vector representation for molecules |
| WO2023047843A1 (ja) | 2021-09-27 | 2023-03-30 | オムロン株式会社 | モデル生成方法、データ提示方法、データ生成方法、推定方法、モデル生成装置、データ提示装置、データ生成装置、及び推定装置 |
| CN116343937A (zh) | 2022-12-28 | 2023-06-27 | 深圳晶泰科技有限公司 | 晶体结构生成方法、装置、电子设备及计算机可读存储介质 |
Non-Patent Citations (1)
| Title |
|---|
| CHIBA, Naoya et al.,"Neural Structure Fields with Application to Crystal Structure Autoencoders",arXiv.org [online],米国,Cornell University,2022年12月08日,[検索日 2024.01.18], pp.1-29,インターネット:<URL:https://arxiv.org/pdf/2012.13120v1.pdf> |
Also Published As
| Publication number | Publication date |
|---|---|
| CN120188167A (zh) | 2025-06-20 |
| JP2025090756A (ja) | 2025-06-17 |
| EP4625255A1 (en) | 2025-10-01 |
| JP2024074765A (ja) | 2024-05-31 |
| WO2024111471A1 (ja) | 2024-05-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Larocca et al. | Barren plateaus in variational quantum computing | |
| JP7187681B2 (ja) | 細胞画像の分析のためのコンピュータ実装方法、コンピュータプログラム製品およびシステム | |
| JP2025090756A (ja) | 情報処理装置、学習済みモデル生成装置、情報処理方法、学習済みモデル生成方法、情報処理プログラム、及び学習済みモデル生成プログラム | |
| Burlina et al. | Where's Wally now? Deep generative and discriminative embeddings for novelty detection | |
| Willett et al. | Minimax optimal level-set estimation | |
| Dhevi | Imputing missing values using Inverse Distance Weighted Interpolation for time series data | |
| Zhang et al. | ET-AL: entropy-targeted active learning for bias mitigation in materials data | |
| Han et al. | AI-powered exploration of molecular vibrations, phonons, and spectroscopy | |
| CN119691673B (zh) | 一种基于多维数据分析的交互数据处理方法 | |
| Chiba et al. | Neural structure fields with application to crystal structure autoencoders | |
| Lee et al. | Methodological framework for materials discovery using machine learning | |
| CN120655990A (zh) | 基于多模态数据和残差图注意力网络的生物特征分析系统 | |
| Qiao et al. | Using the KDE method to model ecological niches: A response to Blonder et al.(2017) | |
| Li et al. | Efficient level-crossing probability calculation for Gaussian process modeled data | |
| CN119649080A (zh) | 一种跨域小样本学习高光谱图像分类方法 | |
| Duta et al. | SPHINX: Structural prediction using hypergraph inference network | |
| Li et al. | Imaging by unsupervised feature learning of the wave equation | |
| JP4451332B2 (ja) | 類似時系列データ計算装置、および類似時系列データ計算プログラム | |
| Saxena et al. | Scalable inference for bayesian multinomial logistic-normal dynamic linear models | |
| Vu et al. | iPMDS: Interactive probabilistic multidimensional scaling | |
| Chavelli | Data-Driven Discovery of State Variables from Dynamical System Observations | |
| Sundararaghavan et al. | Methodology for estimation of intrinsic dimensions and state variables of microstructures | |
| Moi et al. | Quest for new materials: Network theory and machine learning perspectives | |
| Li | Efficient Visualization for Machine-Learning-Represented Scientific Data | |
| Cruz et al. | Image reconstruction in electrical impedance tomography using deep neural networks with differential evolution |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| AA64 | Notification of invalidation of claim of internal priority (with term) |
Free format text: JAPANESE INTERMEDIATE CODE: A241764 Effective date: 20230905 |
|
| A521 | Request for written amendment filed |
Free format text: JAPANESE INTERMEDIATE CODE: A523 Effective date: 20230913 |
|
| A521 | Request for written amendment filed |
Free format text: JAPANESE INTERMEDIATE CODE: A523 Effective date: 20241129 |
|
| A621 | Written request for application examination |
Free format text: JAPANESE INTERMEDIATE CODE: A621 Effective date: 20241129 |
|
| A871 | Explanation of circumstances concerning accelerated examination |
Free format text: JAPANESE INTERMEDIATE CODE: A871 Effective date: 20241129 |
|
| A131 | Notification of reasons for refusal |
Free format text: JAPANESE INTERMEDIATE CODE: A131 Effective date: 20241217 |
|
| A521 | Request for written amendment filed |
Free format text: JAPANESE INTERMEDIATE CODE: A523 Effective date: 20250115 |
|
| TRDD | Decision of grant or rejection written | ||
| A01 | Written decision to grant a patent or to grant a registration (utility model) |
Free format text: JAPANESE INTERMEDIATE CODE: A01 Effective date: 20250212 |
|
| A61 | First payment of annual fees (during grant procedure) |
Free format text: JAPANESE INTERMEDIATE CODE: A61 Effective date: 20250312 |
|
| R150 | Certificate of patent or registration of utility model |
Ref document number: 7655512 Country of ref document: JP Free format text: JAPANESE INTERMEDIATE CODE: R150 |