Makoto Takamoto

Orcid: 0000-0001-7192-1956

According to our database¹, Makoto Takamoto authored at least 24 papers between 2011 and 2025.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

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In proceedings

Article

PhD thesis

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On csauthors.net:

Bibliography

2025

Fast, Modular, and Differentiable Framework for Machine Learning-Enhanced Molecular Simulations.

[BibT_eX]

[DOI]

CoRR, March, 2025

Optimal Embedding Guided Negative Sample Generation for Knowledge Graph Link Prediction.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2025

Active Learning for Neural PDE Solvers.

[BibT_eX]

[DOI]

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Research Data Management in Simulation Science: Infrastructure, Tools, and Applications.

[BibT_eX]

[DOI]

Datenbank-Spektrum, July, 2024

PDEBench Datasets.

[BibT_eX]

[DOI]

Dataset, February, 2024

Physics-Informed Weakly Supervised Learning for Interatomic Potentials.

[BibT_eX]

[DOI]

Makoto Takamoto

Viktor Zaverkin

Mathias Niepert

CoRR, 2024

Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

PDEBench Datasets.

[BibT_eX]

[DOI]

Dataset, November, 2023

PDEBench Pretrained Models.

[BibT_eX]

[DOI]

Dataset, November, 2023

PDEBench Datasets.

[BibT_eX]

[DOI]

Dataset, October, 2023

PDEBench Datasets.

[BibT_eX]

[DOI]

Dataset, September, 2023

PDEBench Datasets.

[BibT_eX]

[DOI]

Dataset, August, 2023

PDEBench Datasets.

[BibT_eX]

[DOI]

Dataset, April, 2023

Learning Neural PDE Solvers with Parameter-Guided Channel Attention.

[BibT_eX]

[DOI]

Makoto Takamoto

Francesco Alesiani

Mathias Niepert

Proceedings of the International Conference on Machine Learning, 2023

2022

PDEBench Datasets.

[BibT_eX]

[DOI]

Dataset, October, 2022

PDEBench Datasets.

[BibT_eX]

[DOI]

Dataset, July, 2022

PDEBench Pretrained Models.

[BibT_eX]

[DOI]

Dataset, June, 2022

PDEBench: An Extensive Benchmark for Scientific Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

MILIE: Modular & Iterative Multilingual Open Information Extraction.

[BibT_eX]

[DOI]

Vanesa Rodriguez-Tembras

Makoto Takamoto

Mathias Niepert

Carolin Lawrence

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

Integrating diverse extraction pathways using iterative predictions for Multilingual Open Information Extraction.

[BibT_eX]

[DOI]

Vanesa Rodriguez-Tembras

Makoto Takamoto

Mathias Niepert

CoRR, 2021

An Empirical Study of the Effects of Sample-Mixing Methods for Efficient Training of Generative Adversarial Networks.

[BibT_eX]

[DOI]

Makoto Takamoto

Yusuke Morishita

Proceedings of the 4th IEEE International Conference on Multimedia Information Processing and Retrieval, 2021

2020

An Efficient Method of Training Small Models for Regression Problems with Knowledge Distillation.

[BibT_eX]

[DOI]

Makoto Takamoto

Yusuke Morishita

Hitoshi Imaoka

Proceedings of the 3rd IEEE Conference on Multimedia Information Processing and Retrieval, 2020

2014

A new scheme of causal viscous hydrodynamics for relativistic heavy-ion collisions: A Riemann solver for quark-gluon plasma.

[BibT_eX]

[DOI]

J. Comput. Phys., 2014

2011

A fast numerical scheme for causal relativistic hydrodynamics with dissipation.

[BibT_eX]

[DOI]

Makoto Takamoto

Shu-ichiro Inutsuka

J. Comput. Phys., 2011

Makoto Takamoto

Timeline

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On csauthors.net:

Bibliography

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