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Computer Science
Japan
2026

D-Index & Metrics

Computer Science

D-Index
106
Citations
62862
World Ranking
272
National Ranking
1

Research.com Recognitions

  • 2026 - Research.com Computer Science in Japan Leader Award
  • 2025 - Research.com Computer Science in Japan Leader Award
  • 2023 - Research.com Computer Science in Japan Leader Award
  • 2022 - Research.com Computer Science in Japan Leader Award
  • 2009 - Polish Academy of Science
  • 1994 - IEEE Fellow For contributions to mathematical foundations of neurocomputing and information geometry.
  • 1992 - Neural Networks Pioneer Award, IEEE Computational Intelligence Society

Overview

Shun-ichi Amari is affiliated with the RIKEN Center for Brain Science in Japan. Their research spans multiple fields, primarily in computer science and mathematics, with significant contributions to subfields including artificial intelligence, applied mathematics, statistical and nonlinear physics, computational theory and mathematics, and cognitive neuroscience.

The scientist's work covers a range of research topics highlighting intersections between theoretical and applied areas. Key themes in their publications include:

  • Statistical Mechanics and Entropy
  • Geometric Analysis and Curvature Flows
  • Topological and Geometric Data Analysis
  • Neural Networks and Applications
  • Machine Learning and Extreme Learning Machines (ELM)
  • Point Processes and Geometric Inequalities
  • Morphological Variations and Asymmetry

Shun-ichi Amari has contributed to notable journals and venues frequently used for disseminating research. These venues include:

  • arXiv (Cornell University)
  • Information Geometry
  • Neural Computation
  • Japanese Journal of Mathematics
  • Journal of Statistical Mechanics Theory and Experiment

They have several recent publications demonstrating a focus on theoretical and computational aspects of neural networks and geometry, such as:

  • Information geometry, 2021, Japanese Journal of Mathematics
  • Any Target Function Exists in a Neighborhood of Any Sufficiently Wide Random Network: A Geometrical Perspective, 2020, Neural Computation
  • Universal statistics of Fisher information in deep neural networks: mean field approach, 2020, Journal of Statistical Mechanics Theory and Experiment
  • When Does Preconditioning Help or Hurt Generalization?, 2020, arXiv (Cornell University)
  • Wasserstein statistics in one-dimensional location scale models, 2021, Annals of the Institute of Statistical Mathematics

Shun-ichi Amari has collaborated frequently with several co-authors, including:

  • Ryo Karakida
  • Takeru Matsuda
  • Shotaro Akaho
  • Kotaro Sakamoto
  • Sho Sonoda

Their work has been recognized with multiple awards, such as:

  • Polish Academy of Science, 2009
  • IEEE Fellow, 1994, for contributions to mathematical foundations of neurocomputing and information geometry
  • Neural Networks Pioneer Award, IEEE Computational Intelligence Society, 1992

Best Publications

  • Natural gradient works efficiently in learning

    Shun-ichi Amari

  • Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications

    Andrzej Cichocki;Shun-ichi Amari

  • Methods of information geometry

    Shun-ichi Amari;Hiroshi Nagaoka

  • A New Learning Algorithm for Blind Signal Separation

    Shun-ichi Amari;Andrzej Cichocki;Howard Hua Yang

  • Dynamics of pattern formation in lateral-inhibition type neural fields

    Shun-Ichi Amari

  • Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-way Data Analysis and Blind Source Separation

    Andrzej Cichocki;Rafal Zdunek;Anh Huy Phan;Shun-ichi Amari

  • Differential-geometrical methods in statistics

    Shun-ichi Amari

  • Adaptive blind signal and image processing

    Andrzej Cichocki;Shun-ichi Amari

  • Nonnegative Matrix and Tensor Factorizations

    Andrzej Cichocki;Rafal Zdunek;Anh Huy Phan;Shun-Ichi Amari

  • Improving support vector machine classifiers by modifying kernal functions

    S. Amari;S. Wu

  • Information Geometry and Its Applications

    Shun-ichi Amari

  • Network information criterion-determining the number of hidden units for an artificial neural network model

    N. Murata;S. Yoshizawa;S. Amari

  • Backpropagation and stochastic gradient descent method

    Shun-ichi Amari

  • A Theory of Adaptive Pattern Classifiers

    Shunichi Amari

  • Adaptive blind signal processing-neural network approaches

    S. Amari;A. Cichocki

  • Learning Patterns and Pattern Sequences by Self-Organizing Nets of Threshold Elements

    S.-I. Amari

  • Adaptive online learning algorithms for blind separation: maximum entropy and minimum mutual information

    Howard Hua Yang;Shun-ichi Amari

  • Statistical neurodynamics of associative memory

    Shun-Ichi Amari;Kenjiro Maginu

  • Flexible Independent Component Analysis

    Seungjin Choi;Andrzej Cichocki;Shun-Ichi Amari

  • Differential Geometry of Curved Exponential Families-Curvatures and Information Loss

    Shun-Ichi Amari

Frequent Co-Authors

Andrzej Cichocki
Andrzej Cichocki Systems Research Institute
Toshiyuki Tanaka
Toshiyuki Tanaka Kyoto University
Naoki Masuda
Naoki Masuda University at Buffalo, State University of New York
Kenji Fukumizu
Kenji Fukumizu The Institute of Statistical Mathematics
Frank Nielsen
Frank Nielsen Sony Computer Science Laboratories
Klaus-Robert Müller
Klaus-Robert Müller Technical University of Berlin
Jianfeng Feng
Jianfeng Feng Fudan University
Yuanqing Li
Yuanqing Li South China University of Technology
Scott C. Douglas
Scott C. Douglas Southern Methodist University

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