Rio Yokota

1.8k total citations
65 papers, 816 citations indexed

About

Rio Yokota is a scholar working on Atomic and Molecular Physics, and Optics, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Rio Yokota has authored 65 papers receiving a total of 816 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Atomic and Molecular Physics, and Optics, 18 papers in Artificial Intelligence and 16 papers in Computational Mechanics. Recurrent topics in Rio Yokota's work include Electromagnetic Scattering and Analysis (30 papers), Parallel Computing and Optimization Techniques (13 papers) and Electromagnetic Simulation and Numerical Methods (11 papers). Rio Yokota is often cited by papers focused on Electromagnetic Scattering and Analysis (30 papers), Parallel Computing and Optimization Techniques (13 papers) and Electromagnetic Simulation and Numerical Methods (11 papers). Rio Yokota collaborates with scholars based in Japan, United States and Saudi Arabia. Rio Yokota's co-authors include Lorena A. Barba, Kenji Yasuoka, Matthew G. Knepley, Tetsu Narumi, Tsuyoshi Hamada, Shinnosuke Obi, Makoto Taiji, Keigo Nitadori, Jaydeep P. Bardhan and Kazuki Osawa and has published in prestigious journals such as The Journal of Chemical Physics, SHILAP Revista de lepidopterología and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Rio Yokota

61 papers receiving 784 citations

Peers

Countries citing papers authored by Rio Yokota

Since Specialization

Citations

This map shows the geographic impact of Rio Yokota's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Rio Yokota with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rio Yokota more than expected).

Fields of papers citing papers by Rio Yokota

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rio Yokota. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Rio Yokota. The network helps show where Rio Yokota may publish in the future.

Co-authorship network of co-authors of Rio Yokota

This figure shows the co-authorship network connecting the top 25 collaborators of Rio Yokota. A scholar is included among the top collaborators of Rio Yokota based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Rio Yokota. Rio Yokota is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	DGEMM on integer matrix multiplication unit 2024 ·The International Journal of High Performance Computing Applications ·(unknown), (unknown), Rio Yokota	10
2	Towards real-time formula driven dataset feed for large scale deep learning training 2023 ·Electronic Imaging ·(unknown), Rio Yokota	2
3	Scalable Linear Time Dense Direct Solver for 3-D Problems without Trailing Sub-Matrix Dependencies 2022 ·(unknown), (unknown), Rio Yokota	1
4	RePOSE: Fast 6D Object Pose Refinement via Deep Texture Rendering 2021 ·2021 IEEE/CVF International Conference on Computer Vision (ICCV) ·(unknown), (unknown), Rawal Khirodkar, Rio Yokota, Kris Kitani	51
5	Practical Deep Learning with Bayesian Principles 2019 ·arXiv (Cornell University) ·Kazuki Osawa, Siddharth Swaroop, Mohammad Emtiyaz Khan, (unknown), (unknown), Richard E. Turner, Rio Yokota	15
6	Analyzing Performance of BiCGStab with Hierarchical Matrix on GPU Clusters 2018 ·Tokyo Tech Research Repository (Tokyo Institute of Technology) ·Ichitaro Yamazaki, Ahmad Abdelfattah, (unknown), Satoshi Ohshima, Stanimire Tomov, Rio Yokota, Jack Dongarra	1
7	Accelerating Matrix Multiplication in Deep Learning by Using Low-Rank Approximation 2017 ·Kazuki Osawa, Akira Sekiya, (unknown), Rio Yokota	13
8	Tapas: An Implicitly Parallel Programming Framework for Hierarchical N-Body Algorithms 2016 ·Tokyo Tech Research Repository (Tokyo Institute of Technology) ·(unknown), Motohiko Matsuda, Naoya Maruyama, Rio Yokota, Kenjiro Taura, Satoshi Matsuoka	2
9	A performance model for the communication in fast multipole methods on high-performance computing platforms 2016 ·The International Journal of High Performance Computing Applications ·(unknown), Rio Yokota, David E. Keyes	4
10	Petascale molecular dynamics simulation using the fast multipole method on K computer 2014 ·Computer Physics Communications ·Yousuke Ohno, Rio Yokota, Hiroshi Koyama, Gentaro Morimoto, (unknown), (unknown), Noriaki Okimoto, Yoshinori Hirano, (unknown), Tetsu Narumi, Makoto Taiji	20
11	Weak scaling of parallel FMM vs. FFT up to 4096 processes 2013 ·Figshare ·(unknown), Rio Yokota	0
12	Hierarchical subdivision of space in FMM (fast multipole method) 2013 ·Figshare ·Rio Yokota, (unknown)	0
13	An FMM Based on Dual Tree Traversal for Many-Core Architectures 2013 ·SHILAP Revista de lepidopterología ·Rio Yokota	22
14	Scaling fast multipole methods up to 4000 GPUs 2012 ·IEEE International Conference on High Performance Computing, Data, and Analytics ·Rio Yokota, Lorena A. Barba, Tetsu Narumi, Kenji Yasuoka	1
15	Towards a Dataflow FMM using the OmpSs Programming Model 2012 ·(unknown), (unknown), (unknown), Naoya Maruyama, Rio Yokota, Satoshi Matsuoka	1
16	ExaFMM: An open source library for Fast Multipole Methods aimed towards Exascale systems 2012 ·Figshare ·(unknown), Rio Yokota	3
17	A tuned and scalable fast multipole method as a preeminent algorithm for exascale systems 2012 ·The International Journal of High Performance Computing Applications ·Rio Yokota, Lorena A. Barba	42
18	Fast N-body Simulations on GPUs 2011 ·arXiv (Cornell University) ·Rio Yokota, Lorena A. Barba	2
19	The study of colliding vortex rings using a special-purpose computer and FMM ⁄ 2008 ·(unknown), Rio Yokota, Kenji Yasuoka, Shinnosuke Obi	4
20	Calculation of isotropic turbulence using a pure Lagrangian vortex method 2007 ·Journal of Computational Physics ·Rio Yokota, (unknown), Shinnosuke Obi	25

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact