◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

T. Sakurai

31 papers hereh-index 252.5k citations178 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author8
  • last author21

Across the 31 of 31 papers where every author was matched, so the position is known.

fields
  • cs.LG9
  • hep-lat6
  • math.NA4
  • cond-mat.mtrl-sci3
  • cond-mat.supr-con2
  • nucl-th2
same name
  • T. Sakurai — 23 papers, h 18
  • T. Sakurai — 13 papers, h 38
  • T. Sakurai — 11 papers, h 7
  • T. Sakurai — 2 papers, h 5
  • T. Sakurai — 1 paper, h 1
  • T. Sakurai — 1 paper, h 10

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20092023
most citedStochastic Estimation of Nuclear Level Density in the Nuclear Shell Model: An Application to Parity-Dependent Level Density in 58Ni

34 citations · 227 across the 31 of their papers we have counts for

collaborators
Showing 2018Show all

3 papers · 1 filter

cs.CV2018★ 1 cited

Classification of X-Ray Protein Crystallization Using Deep Convolutional Neural Networks with a Finder Module

Yusei Miura, Tetsuya Sakurai, Claus Aranha +3

Recently, deep convolutional neural networks have shown good results for image recognition. In this paper, we use convolutional neural networks with a finder module, which discover…

physics.comp-ph2018★ 1 cited

Benefits from using mixed precision computations in the ELPA-AEO and ESSEX-II eigensolver projects

Andreas Alvermann, Achim Basermann, Hans-Joachim Bungartz +30

We first briefly report on the status and recent achievements of the ELPA-AEO (Eigenvalue Solvers for Petaflop Applications - Algorithmic Extensions and Optimizations) and ESSEX II…

stat.ML2018★ 3 cited

Spectral feature scaling method for supervised dimensionality reduction

Momo Matsuda, Keiichi Morikuni, Tetsuya Sakurai

Spectral dimensionality reduction methods enable linear separations of complex data with high-dimensional features in a reduced space. However, these methods do not always give the…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.