J. Yoshimoto

发表

A Generalized Natural Actor-Critic Algorithm

Junichiro Yoshimoto, Kenji Doya, Tetsuro Morimura, 2009, NIPS.

A New Natural Policy Gradient by Stationary Distribution Metric

Junichiro Yoshimoto, Kenji Doya, Tetsuro Morimura, 2008, ECML/PKDD.

Policy gradient reinforcement learning with log stationary distribution gradients

K. Doya, Tetsuro Morimura, E. Uchibe, 2007 .

Control of exploitation-exploration meta-parameter in reinforcement learning

Junichiro Yoshimoto, Shin Ishii, Wako Yoshida, 2002, Neural Networks.

Sparse kernel canonical correlation analysis for discovery of nonlinear interactions in high-dimensional data

Junichiro Yoshimoto, Kenji Doya, Kosuke Yoshida, 2017, BMC Bioinformatics.

Toward Probabilistic Diagnosis and Understanding of Depression Based on Functional MRI Data Analysis with Logistic Group LASSO

Kenji Doya, Junichiro Yoshimoto, Yasumasa Okamoto, 2015, PloS one.

Self-consistent neuronal population under spike inputs and unbalanced conditions

Kenji Doya, Carlos E. Gutierrez, Junichiro Yoshimoto, 2015, 2015 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS).

Connectivity inference from neural recording data: Challenges, mathematical bases and research directions

Junichiro Yoshimoto, Kenji Doya, Ildefons Magrans de Abril, 2017, Neural Networks.

Calcium Responses Model in Striatum Dependent on Timed Input Sources

Junichiro Yoshimoto, Kenji Doya, Jeffery R. Wickens, 2009, ICANN.

A reinforcement learning approach to the shepherding task using SARSA

Junichiro Yoshimoto, Kazushi Ikeda, Clark Kendrick Go, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

Resting state functional connectivity explains individual scores of multiple clinical measures for major depression

Junichiro Yoshimoto, Kenji Doya, Kosuke Yoshida, 2015, 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Bayesian System Identification of Molecular Cascades

Junichiro Yoshimoto, Kenji Doya, K. Doya, 2007, ICONIP.

Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions

Kenji Doya, Junichiro Yoshimoto, Yasumasa Okamoto, 2015, PloS one.

Balance between dopamine and adenosine signals regulates the PKA/Rap1 pathway in striatal medium spiny neurons

J. Yoshimoto, Takashi Nakano, K. Kaibuchi, 2019, Neurochemistry International.

A Spiking Neural Network Model of Model-Free Reinforcement Learning with High-Dimensional Sensory Input and Perceptual Ambiguity

Kenji Doya, Takashi Nakano, Junichiro Yoshimoto, 2015, PloS one.

Brain/MINDS Beyond Human Brain MRI Project: A Protocol for Multi-Site Harmonization across Brain Disorders Throughout the Lifespan

Saori C. Tanaka, D. V. van Essen, M. Kawato, 2020, bioRxiv.

Development of a classifier for gambling disorder based on functional connections between brain regions

M. Kawato, J. Yoshimoto, T. Yoshioka, 2022, Psychiatry and clinical neurosciences.

Enhancing Multi-Center Generalization of Machine Learning-Based Depression Diagnosis From Resting-State fMRI

J. Yoshimoto, Y. Okamoto, S. Yamawaki, 2019, Frontiers in Psychiatry.

Enhancing Multi-Center Generalization of Machine Learning-Based Depression Diagnosis From Resting-State fMRI

J. Yoshimoto, Y. Okamoto, S. Yamawaki, 2019, Frontiers in Psychiatry.

Remote control of neural function by X-ray-induced scintillation

A. Yamanaka, J. Yoshimoto, S. Tsunoda, 2019, Nature Communications.

Importance of the Habenula for Avoidance Learning Including Contextual Cues in the Human Brain: A Preliminary fMRI Study

J. Yoshimoto, Y. Okamoto, S. Yamawaki, 2020, Frontiers in Human Neuroscience.

Dynamics of Basal Ganglia and Thalamus in Parkinsonian Tremor

K. Doya, J. Yoshimoto, J. Morén, 2019, Springer Series in Cognitive and Neural Systems.

Primary motor cortex drives expressive facial movements related to reward processing in mice

A. Yamanaka, J. Yoshimoto, C. Petersen, 2022, bioRxiv.

Sparse kernel canonical correlation analysis for discovery of nonlinear interactions in high-dimensional data

K. Doya, J. Yoshimoto, Kosuke Yoshida, 2017, BMC Bioinformatics.

Balancing plasticity and stability of on-line learning based on hierarchical Bayesian adaptation of forgetting factors

Shin Ishii, Junichiro Hirayama, Junichiro Yoshimoto, 2006, Neurocomputing.

Brain/MINDS beyond human brain MRI project: A protocol for multi-level harmonization across brain disorders throughout the lifespan

Saori C. Tanaka, M. Kawato, J. Yoshimoto, 2021, NeuroImage: Clinical.

Derivatives of Logarithmic Stationary Distributions for Policy Gradient Reinforcement Learning

Junichiro Yoshimoto, Jan Peters, Kenji Doya, 2010, Neural Computation.

System Identification Based on Online Variational Bayes Method and Its Application to Reinforcement Learning

Junichiro Yoshimoto, Shin Ishii, Masa-aki Sato, 2003, ICANN.

A model-based prediction of the calcium responses in the striatal synaptic spines depending on the timing of cortical and dopaminergic inputs and post-synaptic spikes

Junichiro Yoshimoto, Kenji Doya, Takashi Nakano, 2013, Front. Comput. Neurosci..

A Kinetic Model of Dopamine- and Calcium-Dependent Striatal Synaptic Plasticity

Junichiro Yoshimoto, Kenji Doya, Takashi Nakano, 2010, PLoS Comput. Biol..

Bayesian representation learning in the cortex regulated by acetylcholine

Shin Ishii, Junichiro Hirayama, Junichiro Yoshimoto, 2004, Neural Networks.

Model-based action planning involves cortico-cerebellar and basal ganglia networks

Makoto Ito, Kenji Doya, Junichiro Yoshimoto, 2016, Scientific Reports.

25th Annual Computational Neuroscience Meeting: CNS-2016

Morten L. Kringelbach, Majid Nili Ahmadabadi, Anders M. Dale, 2016, BMC Neuroscience.

Multiple clustering for identifying subject clusters and brain sub-networks using functional connectivity matrices without vectorization

Junichiro Yoshimoto, Okito Yamashita, Tomoki Tokuda, 2020, Neural Networks.

Identification of depression subtypes and relevant brain regions using a data-driven approach

Kenji Doya, Junichiro Yoshimoto, Yasumasa Okamoto, 2018, Scientific Reports.

Personality classification enhances blood metabolome analysis and biotyping for major depressive disorders: two-species investigation.

Takahiro A. Kato, J. Yoshimoto, Y. Okamoto, 2020, Journal of affective disorders.

KANPHOS: A Database of Kinase-Associated Neural Protein Phosphorylation in the Brain

J. Yoshimoto, K. Kaibuchi, M. Amano, 2021, Cells.

Statistical analysis on characteristic whisker movements observed in reward processing

Kazushi Ikeda, Junichiro Yoshimoto, Jumpei Ozaki, 2019, 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC).

Evidence for Model-Based Action Planning in a Sequential Finger Movement Task

Makoto Ito, Kenji Doya, Junichiro Yoshimoto, 2010, Journal of motor behavior.

Phosphoproteomics of the Dopamine Pathway Enables Discovery of Rap1 Activation as a Reward Signal In Vivo

Masahiko Watanabe, J. Yoshimoto, A. Nishi, 2016, Neuron.

Clustering of Multiple Psychiatric Disorders Using Functional Connectivity in the Data-Driven Brain Subnetwork

J. Yoshimoto, O. Yamashita, T. Tokuda, 2021, Frontiers in Psychiatry.

Multiple-view clustering for correlation matrices based on Wishart mixture model pdf

Junichiro Yoshimoto, Tomoki Tokuda, Okito Yamashita, 2020, ArXiv.

The Psychological Impact of ‘Mild Lockdown’ in Japan during the COVID-19 Pandemic: A Nationwide Survey under a Declared State of Emergency

J. Yoshimoto, E. Murillo-Rodríguez, C. Uchiumi, 2020, medRxiv.

Learning task-agnostic and interpretable subsequence-based representation of time series and its applications in fMRI analysis

J. Yoshimoto, O. Yamashita, Wenjun Bai, 2023, Neural Networks.

Phosphorylation Signals in Striatal Medium Spiny Neurons.

J. Yoshimoto, K. Kaibuchi, T. Nagai, 2016, Trends in pharmacological sciences.

Modeling Heterogeneous Brain Dynamics of Depression and Melancholia Using Energy Landscape Analysis

Paul Rossener Regonia, Alan S. R. Fermin, J. Yoshimoto, 2021, Frontiers in Psychiatry.

Hierarchical Model Selection for NGnet Based on Variational Bayes Inference

Junichiro Yoshimoto, Shin Ishii, Masa-aki Sato, 2002, ICANN.

Prediction of clinical depression scores and detection of changes in whole-brain using resting-state functional MRI data with partial least squares regression

Kenji Doya, Kosuke Yoshida, Junichiro Yoshimoto, 2017, PloS one.

Data-driven categorization of postoperative delirium symptoms using unsupervised machine learning

J. Yoshimoto, Teruhiko Yoshida, K. Ikeda, 2023, Frontiers in Psychiatry.

Neural mechanisms underlying uninstructed orofacial movements during reward-based learning behaviors

A. Yamanaka, J. Yoshimoto, C. Petersen, 2023, Current Biology.

Resting-state brain activity can predict target-independent aptitude in fMRI-neurofeedback training

M. Machizawa, J. Yoshimoto, Y. Okamoto, 2021, NeuroImage.

Acrobot control by learning the switching of multiple controllers

Junichiro Yoshimoto, Shin Ishii, Yoichi Tokita, 2005, Artificial Life and Robotics.

Engineering a data processing pipeline for an ultra-lightweight lensless fluorescence imaging device with neuronal-cluster resolution

J. Yoshimoto, J. Ohta, K. Ikeda, 2023, Artificial Life and Robotics.

Empirical Bayesian significance measure of neuronal spike response

Yuji Ikegaya, Ken Nakae, Shin Ishii, 2016, BMC Neuroscience.

Leveraging Longitudinal Lifelog Data Using Survival Models for Predicting Risk of Relapse among Patients with Depression in Remission

Kazushi Ikeda, Junichiro Yoshimoto, Toshi A. Furukawa, 2021, 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

Maximum Credibility Voting (MCV) An Integrative Approach for Accurate Diagnosis of Major Depressive Disorder from Clinically Readily Available Data

K. Doya, J. Yoshimoto, Y. Okamoto, 2020, 2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC).

A solving method for MDPs by minimizing variational free energy

J. Yoshimoto, S. Ishii, S. Ishii, 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

On-line EM reinforcement learning

Junichiro Yoshimoto, Shin Ishii, Masa-aki Sato, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

On-Line EM Reinforcement Learning for Automatic Control of Continuous Dynamical Systems

Junichiro Yoshimoto, Shin Ishii, Masa-aki Sato, 2003 .

Application of reinforcement learning to balancing of Acrobot

Junichiro Yoshimoto, Shin Ishii, M. Sato, 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

Normalized Gaussian Network Based on Variational Bayes Inference and Hierarchical Model Selection

Junichiro Yoshimoto, Shin Ishii, Masa-aki Sato, 2003 .

A reinforcement learning for continuous systems

Junichiro Yoshimoto, Shin Ishii, Masa-aki Sato, 2000 .

Reconstructing Temporal Dynamics of fMRI Time Series via Encoded Contextual Information

Okito Yamashita, Wenjun Bai, Tomoki Tokuda, 2020, 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Toward the Perfect Stroke: A Multimodal Approach for Table Tennis Stroke Evaluation

Kazushi Ikeda, Junichiro Yoshimoto, Felan Carlo C. Garcia, 2021, 2021 Thirteenth International Conference on Mobile Computing and Ubiquitous Network (ICMU).