Publications in collaboration with Panasonic members
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IEEE/RSJ International Conference on Intelligent Robots and Systems（IROS）2024
A Contact Model based on Denoising Diffusion to Learn Variable Impedance Control for Contact-rich Manipulation
Masashi Okada, Mayumi Komatsu and Tadahiro Taniguchi
arXiv: https://arxiv.org/abs/2403.13221 -
International Conference on Computer Vision (ICCV) 2023
Representation Uncertainty in Self-Supervised Learning as Variational Inference
Hiroki Nakamura, Masashi Okada and Tadahiro Taniguchi
URL: https://openaccess.thecvf.com/content/ICCV2023/html/Nakamura_Representation_Uncertainty_in_Self-Supervised_Learning_as_Variational_Inference_ICCV_2023_paper.html -
International Conference on Intelligent Robots and Systems (IROS) 2023
Learning Compliant Stiffness by Impedance Control-Aware Task Segmentation and Multi-Objective Bayesian Optimization with Priors
Masashi Okada, Mayumi Komatsu, Ryo Okumura , Tadahiro Taniguchi
arXiv: https://arxiv.org/abs/2307.15345 -
The 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2023)
Online Re-Planning and Adaptive Parameter Update for Multi-Agent Path Finding with Stochastic Travel Times
Atsuyoshi Kita, Nobuhiro Suenari, Masashi Okada and Tadahiro Taniguchi
arXiv: https://arxiv.org/abs/2302.01489 -
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2022
DreamingV2: Reinforcement Learning with Discrete World Models without Reconstruction
Masashi Okada, Tadahiro Taniguchi
Link: https://arxiv.org/abs/2203.00494 -
arXiv:2203.11437
Self-Supervised Representation Learning as Multimodal Variational Inference
Hiroki Nakamura, Masashi Okada, Tadahiro Taniguchi
Link: https://arxiv.org/abs/2203.11437 -
IEEE International Conference on Robotics and Automation (ICRA) 2021
Dreaming: Model-based Reinforcement Learning by Latent Imagination without Reconstruction
Masashi Okada, Tadahiro Taniguchi
Link: https://arxiv.org/abs/2007.14535 -
PLOS ONE
Panacea: Visual exploration system for analyzing trends in annual recruitment using time-varying graphs
Toshiyuki Yokoyama, Masashi Okada, Tadahiro Taniguchi
Link: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0247587 -
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2020 ※採択率：47%
PlaNet of the Bayesians: Reconsidering and Improving Deep Planning Network by Incorporating Bayesian Inference
Masashi Okada, Norio Kosaka, Tadahiro Taniguchi
Link: https://arxiv.org/abs/2003.00370 -
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2020 ※採択率：47%
Domain-Adversarial and -Conditional State Space Model for Imitation Learning
Ryo Okumura, Masashi Okada, Tadahiro Taniguchi
Link: https://arxiv.org/abs/2001.11628 -
IEEE International Conference on Robotics and Automation (ICRA 2020) ※採択率：42% (1,483/3,512)
Multi-person Pose Tracking using Sequential Monte Carlo with Probabilistic Neural Pose Predictor
Masashi Okada, Shinji Takenaka, Tadahiro Taniguchi
Link: https://arxiv.org/abs/1909.07031 -
Conference on Robot Learning (CoRL 2019) ※採択率：28% (110/398)
Variational Inference MPC for Bayesian Model-based Reinforcement Learning
Masashi Okada, Tadahiro Taniguchi
Link: https://arxiv.org/abs/1907.04202 -
IEEE International Conference on Robotics and Automation (ICRA) 2018 ※採択率：40.6% (1,030/2539)
Acceleration of Gradient-based Path Integral Method for Efficient Optimal and Inverse Optimal Control
Masashi Okada, Tadahiro Taniguchi
Link: https://arxiv.org/abs/1710.06578 -
Data Science and Big Data Analytics (DSBDA), IEEE International Conference on Data Mining Workshop (ICDMW 2018)
An Extension of Gradient Boosted Decision Tree Incorporating Statistical Tests
Ryuji Sakata, Iku Ohama, Tadahiro Taniguchi
Link: https://ieeexplore.ieee.org/document/8637438