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Naoki Masuyama

As seen in: Wiley Online Library, arXiv, MDPI
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Articles

Design of Thermotropic Liquid Crystal Molecules With a Wide Temperature Range for the Liquid Crystal Phase Using Machine Learning

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By Naoki Masuyama, Hiromasa Kaneko
| Wiley Online Library Verified
Conflicts of Interest The authors declare no conflicts of interest. Data Availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request. References 1, , , and , “An Up-to-Date Overview of Liquid Crystals and Liquid Crystal Polymers for Different Applications: A Review,” Polymers 16, no. 16 (2024): 2293, https://doi.org/10.3390/polym16162293.
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MLATC: Fast Hierarchical Topological Mapping from 3D LiDAR Point Clouds Based on Adaptive Resonance Theory

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By Yuichiro Toda, Naoki Masuyama, Takayuki Matsuno
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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[2407.08973] Integrating White and Black Box Techniques for Interpretable Machine Learning

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By Naoki Masuyama, Yusuke Nojima
| arXiv
arXiv:2407.08973 (cs) View PDF HTML (experimental) Comments: Subjects: Machine Learning (cs.LG) Cite as: arXiv:2407.08973 [cs.LG] (or arXiv:2407.08973v1 [cs.LG] for this version) Submission history From: Yusuke Nojima [ view email] [v1] Fri, 12 Jul 2024 03:58:04 UTC (1,238 KB) Bibliographic Tools Bibliographic Explorer Toggle Bibliographic Explorer () Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Links to Code...
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