学会発表・論文(パナソニック関連)
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											IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS)2024A 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
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											International Conference on Computer Vision (ICCV) 2023Representation 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
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											International Conference on Intelligent Robots and Systems (IROS) 2023Learning 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
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											IROS 2023 Workshop on World Models and Predictive Coding in Cognitive RoboticsWorld-Model-Based Control for Industrial box-packing of Multiple Objects using NewtonianVAE Yusuke Kato,Ryo Okumura , Tadahiro Taniguchi 
 arXiv: https://arxiv.org/abs/2308.02136
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											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
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											IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2022Tactile-Sensitive NewtonianVAE for High-Accuracy Industrial Connector Insertion Ryo Okumura, Nobuki Nishio, Tadahiro Taniguchi 
 Link: https://arxiv.org/abs/2203.05955
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											IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2022DreamingV2: Reinforcement Learning with Discrete World Models without Reconstruction Masashi Okada, Tadahiro Taniguchi 
 Link: https://arxiv.org/abs/2203.00494
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											arXiv:2203.11437Self-Supervised Representation Learning as Multimodal Variational Inference Hiroki Nakamura, Masashi Okada, Tadahiro Taniguchi 
 Link: https://arxiv.org/abs/2203.11437
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											IEEE International Conference on Robotics and Automation (ICRA) 2021Dreaming: Model-based Reinforcement Learning by Latent Imagination without Reconstruction Masashi Okada, Tadahiro Taniguchi 
 Link: https://arxiv.org/abs/2007.14535
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											PLOS ONEPanacea: 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
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											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
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											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
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											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
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											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
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											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
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											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
 
								