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Junichiro Yoshimoto
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2020 – today
- 2023
- [j16]Chie Hieida
, Tomoaki Yamamoto, Takatomi Kubo, Junichiro Yoshimoto, Kazushi Ikeda:
Negative emotion recognition using multimodal physiological signals for advanced driver assistance systems. Artif. Life Robotics 28(2): 388-393 (2023) - [j15]Zihao Yu, Mark Christian Guinto, Brian Godwin S. Lim
Engineering a data processing pipeline for an ultra-lightweight lensless fluorescence imaging device with neuronal-cluster resolution. Artif. Life Robotics 28(3): 483-495 (2023) - [j14]Wenjun Bai
Learning task-agnostic and interpretable subsequence-based representation of time series and its applications in fMRI analysis. Neural Networks 163: 327-340 (2023) - [c20]Zhongluo Li, Junichiro Yoshimoto, Kazushi Ikeda:
Temporal Attention for Robust Multiple Object Pose Tracking. ICONIP (4) 2023: 551-561 - 2021
- [j13]Takashi Nakano, Masahiro Takamura
Resting-state brain activity can predict target-independent aptitude in fMRI-neurofeedback training. NeuroImage 245: 118733 (2021) - [j12]Tomoki Tokuda
Multiple clustering for identifying subject clusters and brain sub-networks using functional connectivity matrices without vectorization. Neural Networks 142: 269-287 (2021) - [c19]Takuma Kuroki, Osamu Shouno, Junichiro Yoshimoto:
Semi-Supervised Estimation of Driving Behaviors Using Robust Time-Contrastive Learning. APSIPA ASC 2021: 1363-1366 - [c18]Felan Carlo C. Garcia, Ayumi Hirao, Aran Tajika, Toshi A. Furukawa
Leveraging Longitudinal Lifelog Data Using Survival Models for Predicting Risk of Relapse among Patients with Depression in Remission. EMBC 2021: 2455-2458 - [c17]Panyawut Sri-Iesaranusorn, Felan Carlo C. Garcia, Francis Tiausas, Supatsara Wattanakriengkrai, Kazushi Ikeda, Junichiro Yoshimoto:
Toward the Perfect Stroke: A Multimodal Approach for Table Tennis Stroke Evaluation. ICMU 2021: 1-5 - 2020
- [c16]Panyawut Sri-Iesaranusorn, Saeka Shimochi, Naoki Ono, Emrah Yatkin, Hidehiro Iida, Kazushi Ikeda, Junichiro Yoshimoto:
Quantification Analysis of Behavioral Changes after Sciatic Nerve Ligation in Rats. APSIPA 2020: 952-957 - [c15]Yu Shimizu, Junichiro Yoshimoto, Masahiro Takamura, Go Okada, Tomoya Matsumoto, Manabu Fuchikami, Satoshi Okada, Shigeru Morinobu, Yasumasa Okamoto, Shigeto Yamawaki, Kenji Doya:
Maximum Credibility Voting (MCV) An Integrative Approach for Accurate Diagnosis of Major Depressive Disorder from Clinically Readily Available Data. APSIPA 2020: 1023-1032 - [c14]Wenjun Bai
Reconstructing Temporal Dynamics of fMRI Time Series via Encoded Contextual Information. BIBM 2020: 968-971 - [i1]Tomoki Tokuda, Okito Yamashita, Junichiro Yoshimoto:
Multiple-view clustering for correlation matrices based on Wishart mixture model. CoRR abs/2010.09941 (2020)
2010 – 2019
- 2019
- [c13]Junichiro Yoshimoto, Jumpei Ozaki, Kohta Mizutani, Takashi Nakano
Statistical analysis on characteristic whisker movements observed in reward processing. APSIPA 2019: 723-726 - 2018
- [j11]Ildefons Magrans de Abril, Junichiro Yoshimoto
Connectivity inference from neural recording data: Challenges, mathematical bases and research directions. Neural Networks 102: 120-137 (2018) - 2017
- [j10]Kosuke Yoshida
Sparse kernel canonical correlation analysis for discovery of nonlinear interactions in high-dimensional data. BMC Bioinform. 18(1): 108:1-108:11 (2017) - 2016
- [c12]Clark Kendrick Go, Bryan Lao, Junichiro Yoshimoto
A reinforcement learning approach to the shepherding task using SARSA. IJCNN 2016: 3833-3836 - 2015
- [c11]Kosuke Yoshida, Yu Shimizu, Junichiro Yoshimoto
Resting state functional connectivity explains individual scores of multiple clinical measures for major depression. BIBM 2015: 1078-1083 - [c10]JeongHun Baek, Shigeyuki Oba, Junichiro Yoshimoto
Computational Complexity Reduction for Functional Connectivity Estimation in Large Scale Neural Network. ICONIP (3) 2015: 583-591 - 2013
- [j9]Takashi Nakano
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. Frontiers Comput. Neurosci. 7: 119 (2013) - 2011
- [j8]Junichiro Yoshimoto
Bayesian Normalized Gaussian Network and Hierarchical Model Selection Method. Intell. Autom. Soft Comput. 17(1): 71-94 (2011) - 2010
- [j7]Tetsuro Morimura, Eiji Uchibe
Derivatives of Logarithmic Stationary Distributions for Policy Gradient Reinforcement Learning. Neural Comput. 22(2): 342-376 (2010) - [j6]Takashi Nakano
A Kinetic Model of Dopamine- and Calcium-Dependent Striatal Synaptic Plasticity. PLoS Comput. Biol. 6(2) (2010) - [c9]Makoto Otsuka, Junichiro Yoshimoto, Kenji Doya:
Free-energy-based reinforcement learning in a partially observable environment. ESANN 2010
2000 – 2009
- 2009
- [c8]Takashi Nakano
Calcium Responses Model in Striatum Dependent on Timed Input Sources. ICANN (1) 2009: 249-258 - [c7]Tetsuro Morimura, Eiji Uchibe, Junichiro Yoshimoto, Kenji Doya:
A Generalized Natural Actor-Critic Algorithm. NIPS 2009: 1312-1320 - 2008
- [c6]Makoto Otsuka, Junichiro Yoshimoto
Robust Population Coding in Free-Energy-Based Reinforcement Learning. ICANN (1) 2008: 377-386 - [c5]Tetsuro Morimura, Eiji Uchibe, Junichiro Yoshimoto
A New Natural Policy Gradient by Stationary Distribution Metric. ECML/PKDD (2) 2008: 82-97 - 2007
- [c4]Junichiro Yoshimoto
Bayesian System Identification of Molecular Cascades. ICONIP (1) 2007: 614-624 - 2006
- [j5]Junichiro Hirayama, Junichiro Yoshimoto
Balancing plasticity and stability of on-line learning based on hierarchical Bayesian adaptation of forgetting factors. Neurocomputing 69(16-18): 1954-1961 (2006) - 2005
- [j4]Junichiro Yoshimoto
Acrobot control by learning the switching of multiple controllers. Artif. Life Robotics 9(2): 67-71 (2005) - 2004
- [j3]Junichiro Hirayama, Junichiro Yoshimoto
Bayesian representation learning in the cortex regulated by acetylcholine. Neural Networks 17(10): 1391-1400 (2004) - 2003
- [c3]Junichiro Yoshimoto, Shin Ishii, Masa-aki Sato:
System Identification Based on Online Variational Bayes Method and Its Application to Reinforcement Learning. ICANN 2003: 123-131 - 2002
- [j2]Shin Ishii
Control of exploitation-exploration meta-parameter in reinforcement learning. Neural Networks 15(4-6): 665-687 (2002) - [c2]Junichiro Yoshimoto, Shin Ishii, Masa-aki Sato:
Hierarchical Model Selection for NGnet Based on Variational Bayes Inference. ICANN 2002: 661-666 - 2001
- [j1]Junichiro Yoshimoto
Application of reinforcement learning based on on-line EM algorithm to balancing of acrobot. Syst. Comput. Jpn. 32(5): 12-20 (2001) - 2000
- [c1]Junichiro Yoshimoto, Shin Ishii, Masa-aki Sato:
On-Line EM Reinforcement Learning. IJCNN (3) 2000: 163-168
Coauthor Index
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