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Makoto Uemura
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2020 – today
- 2023
- [c10]Issei Fujishiro, Naoko Sawada, Makoto Uemura:
Clustering, Universalities, and Evolutionary Schema Design. EDBT/ICDT Workshops 2023 - 2022
- [j3]Naoko Sawada
, Makoto Uemura
, Issei Fujishiro
:
Multi-dimensional time-series subsequence clustering for visual feature analysis of blazar observation datasets. Astron. Comput. 41: 100663 (2022) - [j2]Naoko Sawada
, Makoto Uemura
, Johanna Beyer
, Hanspeter Pfister
, Issei Fujishiro
:
TimeTubesX: A Query-Driven Visual Exploration of Observable, Photometric, and Polarimetric Behaviors of Blazars. IEEE Trans. Vis. Comput. Graph. 28(4): 1917-1929 (2022) - 2020
- [c9]Rikuo Uchiki, Malik Olivier Boussejra, Liyu Zhu, Yuriko Takeshima, Kazuya Matsubayashi, Makoto Uemura, Issei Fujishiro:
Accurate Visualization of Galaxy Velocity Fields from Three-Dimensional Integral Field Spectroscopy Data. EuroVis (Posters) 2020: 37-39
2010 – 2019
- 2019
- [j1]Malik Olivier Boussejra, Rikuo Uchiki, Yuriko Takeshima, Kazuya Matsubayashi, Shunya Takekawa
, Makoto Uemura
, Issei Fujishiro:
aflak: Visual programming environment enabling end-to-end provenance management for the analysis of astronomical datasets. Vis. Informatics 3(1): 1-8 (2019) - 2018
- [c8]Naoko Sawada, Masanori Nakayama, Makoto Uemura
, Issei Fujishiro:
TimeTubes: Automatic Extraction of Observable Blazar Features from Long-Term, Multi-Dimensional Datasets. SciVis 2018: 67-71 - [c7]Malik Olivier Boussejra, Kazuya Matsubayashi, Yuriko Takeshima, Shunya Takekawa
, Rikuo Uchiki, Makoto Uemura
, Issei Fujishiro:
aflak: Pluggable Visual Programming Environment with Quick Feedback Loop Tuned for Multi-Spectral Astrophysical Observations. SciVis 2018: 72-76 - 2017
- [c6]Hsiang-Yun Wu, Yusuke Niibe, Kazuho Watanabe
, Shigeo Takahashi, Makoto Uemura
, Issei Fujishiro:
Making many-to-many parallel coordinate plots scalable by asymmetric biclustering. PacificVis 2017: 305-309 - [c5]Naoko Sawada, Masanori Nakayama, Hsiang-Yun Wu, Makoto Uemura
, Issei Fujishiro:
TimeTubes: visual fusion and validation for ameliorating uncertainties of blazar datasets from different observatories. CGI 2017: 14:1-14:6 - 2016
- [c4]Yoshiyuki Kabashima, Tomoyuki Obuchi, Makoto Uemura
:
Approximate cross-validation formula for Bayesian linear regression. Allerton 2016: 596-600 - [i1]Yoshiyuki Kabashima, Tomoyuki Obuchi, Makoto Uemura:
Approximate cross-validation formula for Bayesian linear regression. CoRR abs/1610.07733 (2016) - 2014
- [c3]Satoshi Tanaka, Makoto Uemura, Kyoko Hasegawa, Takehiko Kitagawa, Takahiro Yoshida, Asuka Sugiyama, Hiromi T. Tanaka, Atsushi Okamoto, Naohisa Sakamoto, Koji Koyamada:
Application of Stochastic Point-Based Rendering to Transparent Visualization of Large-Scale Laser-Scanned Data of 3D Cultural Assets. PacificVis 2014: 267-271 - 2013
- [c2]Shiro Ikeda
, Hirokazu Odaka, Makoto Uemura
, Tadayuki Takahashi, Shin Watanabe, Shin'ichiro Takeda:
Compton camera imaging. ICST 2013: 674-677 - 2011
- [c1]Makoto Uemura, Masatsugu Yamamoto, Satoshi Tanaka, Susumu Nakata
, Kyoko Hasegawa:
Particle-Based Transparent Visualization of 3D Inner Structure of Funeboko in Gion Festival. Culture and Computing 2011: 193-194
Coauthor Index

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