Paper Abstract and Keywords |
Presentation |
2015-11-26 15:00
[Poster Presentation]
Selective sampling by using Gaussian Process and its application to material science Daisuke Hirano (NIT), Kazuaki Toyoura (Nagoya Univ.), Atsuto Seko (Kyoto Univ.), Motoki Shiga (Gifu Univ.), Akihide Kuwabara (JFCC), Masayuki Karasuyama (NIT), Kazuki Shitara (Kyoto Univ.), Ichiro Takeuchi (NIT) IBISML2015-66 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Various physical phenomena and properties of an unknown material are often revealed by exhaustively evaluating the entire potential energy surface (PES) in th configuration space. However, especially when an accurate non-empirical PES evaluation is required, the computational cost of such an exhaustive evaluation is prohibitively large. In this paper, we introduce machine learning-based sampling spproach for reducing the large computational cost which can be used for investigating some specific physical properties. Our key idea is to develop a statistical model of the PES by using emph{Gaussian process (GP)} and use the GP model for selectively evaluating the region of interest that characterizes our target physical properties. We demonstrate the efficacy of the proposed approach by applying it to one of the well-studied proton conduction oxides, ${rm BaZrO_3}$. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Gaussian Process / material informatics / / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 115, no. 323, IBISML2015-66, pp. 99-106, Nov. 2015. |
Paper # |
IBISML2015-66 |
Date of Issue |
2015-11-19 (IBISML) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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IBISML2015-66 |
Conference Information |
Committee |
IBISML |
Conference Date |
2015-11-25 - 2015-11-27 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Epochal Tsukuba |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Information-Based Induction Science Workshop (IBIS2015) |
Paper Information |
Registration To |
IBISML |
Conference Code |
2015-11-IBISML |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Selective sampling by using Gaussian Process and its application to material science |
Sub Title (in English) |
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Gaussian Process |
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material informatics |
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1st Author's Name |
Daisuke Hirano |
1st Author's Affiliation |
Nagoya Institute of Technology (NIT) |
2nd Author's Name |
Kazuaki Toyoura |
2nd Author's Affiliation |
Nagoya University (Nagoya Univ.) |
3rd Author's Name |
Atsuto Seko |
3rd Author's Affiliation |
Kyoto Univesity (Kyoto Univ.) |
4th Author's Name |
Motoki Shiga |
4th Author's Affiliation |
Gifu University (Gifu Univ.) |
5th Author's Name |
Akihide Kuwabara |
5th Author's Affiliation |
Japan Fine Ceramics Center (JFCC) |
6th Author's Name |
Masayuki Karasuyama |
6th Author's Affiliation |
Nagoya Institute of Technology (NIT) |
7th Author's Name |
Kazuki Shitara |
7th Author's Affiliation |
Kyoto Univesity (Kyoto Univ.) |
8th Author's Name |
Ichiro Takeuchi |
8th Author's Affiliation |
Nagoya Institute of Technology (NIT) |
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Speaker |
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Date Time |
2015-11-26 15:00:00 |
Presentation Time |
180 minutes |
Registration for |
IBISML |
Paper # |
IBISML2015-66 |
Volume (vol) |
vol.115 |
Number (no) |
no.323 |
Page |
pp.99-106 |
#Pages |
8 |
Date of Issue |
2015-11-19 (IBISML) |
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