Heecheol Kim

Orcid: 0000-0002-3451-2288

Affiliations:
  • University of Tokyo, Graduate School of Information Science and Technology, Japan


According to our database1, Heecheol Kim authored at least 13 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
Goal-Conditioned Dual-Action Imitation Learning for Dexterous Dual-Arm Robot Manipulation.
IEEE Trans. Robotics, 2024

Multi-task robot data for dual-arm fine manipulation.
CoRR, 2024

2023
Training Robots Without Robots: Deep Imitation Learning for Master-to-Robot Policy Transfer.
IEEE Robotics Autom. Lett., May, 2023

2022
Robot peels banana with goal-conditioned dual-action deep imitation learning.
CoRR, 2022

Using human gaze in few-shot imitation learning for robot manipulation.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Memory-based gaze prediction in deep imitation learning for robot manipulation.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

2021
Gaze-Based Dual Resolution Deep Imitation Learning for High-Precision Dexterous Robot Manipulation.
IEEE Robotics Autom. Lett., 2021

Transformer-based deep imitation learning for dual-arm robot manipulation.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

2020
Using Human Gaze to Improve Robustness Against Irrelevant Objects in Robot Manipulation Tasks.
IEEE Robotics Autom. Lett., 2020

Reinforcement Learning in Latent Action Sequence Space.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Disentangled Representations for Sequence Data using Information Bottleneck Principle.
Proceedings of The 12th Asian Conference on Machine Learning, 2020

2019
Macro Action Reinforcement Learning with Sequence Disentanglement using Variational Autoencoder.
CoRR, 2019

FAVAE: Sequence Disentanglement using Information Bottleneck Principle.
CoRR, 2019


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