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D-Index & Metrics

Computer Science

D-Index
33
Citations
9758
World Ranking
12382
National Ranking
193

Overview

Motoaki Kawanabe is affiliated with the Advanced Telecommunications Research Institute International in Japan. Their research encompasses a wide range of topics within computer science and neuroscience, focusing on areas related to brain function and machine learning.

The main fields of study include:

  • Computer Science
  • Neuroscience

Key subfields Kawanabe has contributed to are:

  • Cognitive Neuroscience
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Radiology, Nuclear Medicine and Imaging

The principal topics explored in their work cover:

  • Functional Brain Connectivity Studies
  • Neural dynamics and brain function
  • EEG and Brain-Computer Interfaces
  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Topic Modeling
  • Neural Networks and Applications

Kawanabe has published extensively, with the majority of papers appearing in venues such as:

  • arXiv (Cornell University)
  • NeuroImage
  • IEEE Access
  • bioRxiv (Cold Spring Harbor Laboratory)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Selected recent publications include:

  • "ScanQA: 3D Question Answering for Spatial Scene Understanding," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Asymmetric directed functional connectivity within the frontoparietal motor network during motor imagery and execution," 2021, NeuroImage
  • "Interpretable brain age prediction using linear latent variable models of functional connectivity," 2020, PLoS ONE
  • "Event-related microstate dynamics represents working memory performance," 2022, NeuroImage
  • "SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG," 2022, arXiv (Cornell University)

Frequent collaborators in Kawanabe's research include:

  • Taiki Miyanishi
  • Takeshi OGAWA
  • Jun-ichiro Hirayama
  • Reinmar J. Kobler
  • Shuhei Kurita

Best Publications

  • Optimizing Spatial filters for Robust EEG Single-Trial Analysis

    B. Blankertz;R. Tomioka;S. Lemm;M. Kawanabe

  • How to Explain Individual Classification Decisions

    David Baehrens;Timon Schroeter;Stefan Harmeling;Motoaki Kawanabe

  • Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation

    Masashi Sugiyama;Shinichi Nakajima;Hisashi Kashima;Paul V. Buenau

  • Direct importance estimation for covariate shift adaptation

    Masashi Sugiyama;Taiji Suzuki;Shinichi Nakajima;Hisashi Kashima

  • Machine Learning in Non-Stationary Environments: Introduction to Covariate Shift Adaptation

    Masashi Sugiyama;Motoaki Kawanabe

  • Toward Unsupervised Adaptation of LDA for Brain–Computer Interfaces

    C Vidaurre;M Kawanabe;P von Bünau;B Blankertz

  • Invariant Common Spatial Patterns: Alleviating Nonstationarities in Brain-Computer Interfacing

    Benjamin Blankertz;Motoaki Kawanabe;Ryota Tomioka;Friederike Hohlefeld

  • Stationary common spatial patterns for brain-computer interfacing.

    Wojciech Samek;Carmen Vidaurre;Klaus Robert Müller;Klaus Robert Müller;Motoaki Kawanabe

  • Optimal cluster preserving embedding of nonmetric proximity data

    V. Roth;J. Laub;M. Kawanabe;J.M. Buhmann

  • Divergence-Based Framework for Common Spatial Patterns Algorithms

    Wojciech Samek;Motoaki Kawanabe;Klaus-Robert Muller

  • A New Discriminative Kernel From Probabilistic Models

    Koji Tsuda;Motoaki Kawanabe;Gunnar Rätsch;Sören Sonnenburg

  • How to Explain Individual Classification Decisions

    David Baehrens;Timon Schroeter;Stefan Harmeling;Motoaki Kawanabe

  • Machine Learning in Non-Stationary Environments

    Unknown

  • Kernel-based nonlinear blind source separation

    Stefan Harmeling;Andreas Ziehe;Motoaki Kawanabe;Klaus-Robert Müller

  • A resampling approach to estimate the stability of one-dimensional or multidimensional independent components

    F. Meinecke;A. Ziehe;M. Kawanabe;K.-R. Muller

  • Information geometry of estimating functions in semi-parametric statistical models

    Shun-Ichi Amari;Motoaki Kawanabe

  • Modeling Sparse Connectivity Between Underlying Brain Sources for EEG/MEG

    Stefan Haufe;Ryota Tomioka;Guido Nolte;Klaus-Robert Müller

  • Learning a common dictionary for subject-transfer decoding with resting calibration.

    Hiroshi Morioka;Atsunori Kanemura;Jun-ichiro Hirayama;Manabu Shikauchi

  • ScanQA: 3D Question Answering for Spatial Scene Understanding

    Unknown

  • Blind separation of post-nonlinear mixtures using linearizing transformations and temporal decorrelation

    Andreas Ziehe;Motoaki Kawanabe;Stefan Harmeling;Klaus-Robert Müller

  • In Search of Non-Gaussian Components of a High-Dimensional Distribution

    Gilles Blanchard;Gilles Blanchard;Motoaki Kawanabe;Masashi Sugiyama;Masashi Sugiyama;Vladimir Spokoiny

  • On-line learning in changing environments with applications in supervised and unsupervised learning

    Noboru Murata;Motoaki Kawanabe;Andreas Ziehe;Klaus-Robert Müller

Frequent Co-Authors

Klaus-Robert Müller
Klaus-Robert Müller Technical University of Berlin
Aapo Hyvärinen
Aapo Hyvärinen University of Helsinki
Carmen Vidaurre
Carmen Vidaurre Technical University of Berlin
Koji Tsuda
Koji Tsuda University of Tokyo
Stefan Harmeling
Stefan Harmeling TU Dortmund University
Benjamin Blankertz
Benjamin Blankertz Technical University of Berlin
Shun-ichi Amari
Shun-ichi Amari RIKEN Center for Brain Science
Fabian J. Theis
Fabian J. Theis Technical University of Munich
Vesa Kiviniemi
Vesa Kiviniemi Oulu University Hospital

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