Makoto Takamoto

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 12

Top Topics

Benchmark Suite

Regression Problems

Data Management

Machine Learning Methods

Top Venues

Datenbank-Spektrum

Publications

Viktor Zaverkin, Francesco Alesiani, Takashi Maruyama, Federico Errica, Henrik Christiansen, Makoto Takamoto, Nicolas Weber, Mathias Niepert
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing. CoRR (2024)
Bernd Flemisch, Sibylle Hermann, Melanie Herschel, Dirk Pflüger, Jürgen Pleiss, Jan Range, Sarbani Roy, Makoto Takamoto, Benjamin Uekermann
Research Data Management in Simulation Science: Infrastructure, Tools, and Applications. Datenbank-Spektrum 24 (2) (2024)
Makoto Takamoto, Francesco Alesiani, Mathias Niepert
Learning Neural PDE Solvers with Parameter-Guided Channel Attention. CoRR (2023)
Makoto Takamoto, Francesco Alesiani, Mathias Niepert
Learning Neural PDE Solvers with Parameter-Guided Channel Attention. ICML (2023)
Makoto Takamoto, Timothy Praditia, Raphael Leiteritz, Dan MacKinlay, Francesco Alesiani, Dirk Pflüger, Mathias Niepert
PDEBENCH: An Extensive Benchmark for Scientific Machine Learning. CoRR (2022)
Makoto Takamoto, Timothy Praditia, Raphael Leiteritz, Daniel MacKinlay, Francesco Alesiani, Dirk Pflüger, Mathias Niepert
PDEBench: An Extensive Benchmark for Scientific Machine Learning. NeurIPS (2022)
Bhushan Kotnis, Kiril Gashteovski, Daniel Rubio, Ammar Shaker, Vanesa Rodriguez-Tembras, Makoto Takamoto, Mathias Niepert, Carolin Lawrence
MILIE: Modular & Iterative Multilingual Open Information Extraction. ACL (1) (2022)
Makoto Takamoto, Yusuke Morishita
An Empirical Study of the Effects of Sample-Mixing Methods for Efficient Training of Generative Adversarial Networks. MIPR (2021)
Bhushan Kotnis, Kiril Gashteovski, Carolin Lawrence, Daniel Oñoro-Rubio, Vanesa Rodriguez-Tembras, Makoto Takamoto, Mathias Niepert
Integrating diverse extraction pathways using iterative predictions for Multilingual Open Information Extraction. CoRR (2021)
Makoto Takamoto, Yusuke Morishita
An Empirical Study of the Effects of Sample-Mixing Methods for Efficient Training of Generative Adversarial Networks. CoRR (2021)
Makoto Takamoto, Yusuke Morishita, Hitoshi Imaoka
An Efficient Method of Training Small Models for Regression Problems with Knowledge Distillation. CoRR (2020)
Makoto Takamoto, Yusuke Morishita, Hitoshi Imaoka
An Efficient Method of Training Small Models for Regression Problems with Knowledge Distillation. MIPR (2020)
Yukinao Akamatsu, Shu-ichiro Inutsuka, Chiho Nonaka, Makoto Takamoto
A new scheme of causal viscous hydrodynamics for relativistic heavy-ion collisions: A Riemann solver for quark-gluon plasma. J. Comput. Phys. 256 (2014)
Makoto Takamoto, Shu-ichiro Inutsuka
A fast numerical scheme for causal relativistic hydrodynamics with dissipation. J. Comput. Phys. 230 (18) (2011)