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pro vyhledávání: '"Dam-Hieu P"'
Autor:
Dinh, Tai, Hauchi, Wong, Fournier-Viger, Philippe, Lisik, Daniil, Ha, Minh-Quyet, Dam, Hieu-Chi, Huynh, Van-Nam
The clustering of categorical data is a common and important task in computer science, offering profound implications across a spectrum of applications. Unlike purely numerical data, categorical data often lack inherent ordering as in nominal data, o
Externí odkaz:
http://arxiv.org/abs/2408.17244
As interdisciplinary science is flourishing because of materials informatics and additional factors; a systematic way is required for expressing knowledge and facilitating communication between scientists in various fields. A function decomposition t
Externí odkaz:
http://arxiv.org/abs/2205.00829
Autor:
Nguyen, Duong-Nguyen, Pham, Tien-Lam, Nguyen, Viet-Cuong, Kino, Hiori, Miyake, Takashi, Dam, Hieu-Chi
We propose a data-driven method to extract dissimilarity between materials, with respect to a given target physical property. The technique is based on an ensemble method with Kernel ridge regression as the predicting model; multiple random subset sa
Externí odkaz:
http://arxiv.org/abs/2008.08818
Autor:
Pham, Tien-Lam, Nguyen, Duong-Nguyen, Ha, Minh-Quyet, Kino, Hiori, Miyake, Takashi, Dam, Hieu-Chi
New Nd-Fe-B crystal structures can be formed via the elemental substitution of LATX host structures, including lanthanides LA, transition metals T, and light elements X as B, C, N, and O. The 5967 samples of ternary LATX materials that are collected
Externí odkaz:
http://arxiv.org/abs/2008.08793
In this study, we investigate the structure-stability relationship of hypothetical Nd-Fe-B crystal structures using descriptor-relevance analysis and the t-SNE dimensionality reduction method. 149 hypothetical Nd-Fe-B crystal structures are generated
Externí odkaz:
http://arxiv.org/abs/2008.08781
We propose a framework called HyperVAE for encoding distributions of distributions. When a target distribution is modeled by a VAE, its neural network parameters \theta is drawn from a distribution p(\theta) which is modeled by a hyper-level VAE. We
Externí odkaz:
http://arxiv.org/abs/2005.08482
Akademický článek
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In this study, we establish a basis for selecting similarity measures when applying machine learning techniques to solve materials science problems. This selection is considered with an emphasis on the distinctiveness between materials that reflect t
Externí odkaz:
http://arxiv.org/abs/1903.10867
Akademický článek
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Autor:
Dam, Hieu Chi, Nguyen, Viet Cuong, Pham, Tien Lam, Nguyen, Anh Tuan, Terakura, Kiyoyuki, Miyake, Takashi, Kino, Hiori
We analyze Curie temperatures of rare-earth transition metal binary alloys with machine learning method. In order to select important descriptors and descriptor groups, we introduce newly developed subgroup relevance analysis and adopt the hierarchic
Externí odkaz:
http://arxiv.org/abs/1809.04750