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J. Morimoto

4 papers hereh-index 427.5k citations210 works total

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

author position
  • middle author2
  • last author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.RO2
  • cs.LG1
  • q-bio.NC1

identity via Semantic Scholar / OpenAlex

activity
20132019
most citedIdentifying melancholic depression biomarker using whole-brain functional connectivity

3 citations · 3 across the 2 of their papers we have counts for

collaborators

4 papers

cs.RO2019

Phase Portraits as Movement Primitives for Fast Humanoid Robot Control

Guilherme Maeda, Okan Koc, Jun Morimoto

Currently, usual approaches for fast robot control are largely reliant on solving online optimal control problems. Such methods are known to be computationally intensive and sensit…

cs.RO2019

An Optimal Assistive Control Strategy based on User's Motor Goal Estimation

Jun-ichiro Furukawa, Jun Morimoto

In this study, we propose an optimal assistive control strategy that uses estimated user's movement intention as the terminal cost function. We estimate the movement intention by o…

q-bio.NC2017★ 3 cited

Identifying melancholic depression biomarker using whole-brain functional connectivity

Naho Ichikawa, Giuseppe Lisi, Noriaki Yahata +14

By focusing on melancholic features with biological homogeneity, this study aimed to identify a small number of critical functional connections (FCs) that were specific only to the…

cs.LG2013

Efficient Sample Reuse in Policy Gradients with Parameter-based Exploration

Tingting Zhao, Hirotaka Hachiya, Voot Tangkaratt +2

The policy gradient approach is a flexible and powerful reinforcement learning method particularly for problems with continuous actions such as robot control. A common challenge in…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.