Efficient Motor Babbling Using Variance Predictions from a Recurrent Neural Network. - Kuniyuki Takahashi; Kanata Suzuki; Tetsuya Ogata; Hadi Tjandra; Shigeki Sugano (ICONIP (3), 2015)

Online Motion Generation with Sensory Information and Instructions by Hierarchical RNN. - Kanata Suzuki; Hiroki Mori; Tetsuya Ogata (CoRR, 2017)

Repeatable Folding Task by Humanoid Robot Worker Using Deep Learning. - Pin-Chu Yang; Kazuma Sasaki; Kanata Suzuki; Kei Kase; Shigeki Sugano; Tetsuya Ogata (IEEE Robotics Autom. Lett., 2017)

Put-in-Box Task Generated from Multiple Discrete Tasks by aHumanoid Robot Using Deep Learning. - Kei Kase; Kanata Suzuki; Pin-Chu Yang; Hiroki Mori; Tetsuya Ogata (ICRA, 2018)

Motion Switching With Sensory and Instruction Signals by Designing Dynamical Systems Using Deep Neural Network. - Kanata Suzuki; Hiroki Mori; Tetsuya Ogata (IEEE Robotics Autom. Lett., 2018)

Stable Deep Reinforcement Learning Method by Predicting Uncertainty in Rewards as a Subtask. - Kanata Suzuki; Tetsuya Ogata (ICONIP (2), 2020)

HATSUKI : An anime character like robot figure platform with anime-style expressions and imitation learning based action generation. - Pin-Chu Yang; Mohammed Al-Sada; Chang-Chieh Chiu; Kevin Kuo; Tito Pradhono Tomo; Kanata Suzuki; Nelson Yalta; Kuo-Hao Shu; Tetsuya Ogata (RO-MAN, 2020)

Online Self-Supervised Learning for Object Picking: Detecting Optimum Grasping Position using a Metric Learning Approach. - Kanata Suzuki; Yasuto Yokota; Yuzi Kanazawa; Tomoyoshi Takebayashi (SII, 2020)

A Multi-task Learning Framework for Grasping-Position Detection and Few-Shot Classification. - Yasuto Yokota; Kanata Suzuki; Yuzi Kanazawa; Tomoyoshi Takebayashi (SII, 2020)

Undefined-behavior guarantee by switching to model-based controller according to the embedded dynamics in Recurrent Neural Network. - Kanata Suzuki; Hiroki Mori; Tetsuya Ogata (CoRR, 2020)

Classification of glomerular pathological findings using deep learning and nephrologist-AI collective intelligence approach. - Eiichiro Uchino; Kanata Suzuki; Noriaki Sato; Ryosuke Kojima; Yoshinori Tamada; Shusuke Hiragi; Hideki Yokoi; Nobuhiro Yugami; Sachiko Minamiguchi; Hironori Haga; Motoko Yanagita; Yasushi Okuno (Int. J. Medical Informatics, 2020)

In-air Knotting of Rope using Dual-Arm Robot based on Deep Learning. - Kanata Suzuki; Momomi Kanamura; Yuki Suga; Hiroki Mori; Tetsuya Ogata (IROS, 2021)

Annotation Cost Reduction of Stream-based Active Learning by Automated Weak Labeling using a Robot Arm. - Kanata Suzuki; Taro Sunagawa; Tomotake Sasaki; Takashi Katoh (IROS, 2021)

Three approaches to facilitate DNN generalization to objects in out-of-distribution orientations and illuminations: late-stopping, tuning batch normalization and invariance loss. - Akira Sakai; Taro Sunagawa; Spandan Madan; Kanata Suzuki; Takashi Katoh; Hiromichi Kobashi; Hanspeter Pfister; Pawan Sinha; Xavier Boix; Tomotake Sasaki (CoRR, 2021)

Compensation for Undefined Behaviors During Robot Task Execution by Switching Controllers Depending on Embedded Dynamics in RNN. - Kanata Suzuki; Hiroki Mori; Tetsuya Ogata (IEEE Robotics Autom. Lett., 2021)

Embodying Pre-Trained Word Embeddings Through Robot Actions. - Minori Toyoda; Kanata Suzuki; Hiroki Mori; Yoshihiko Hayashi; Tetsuya Ogata (IEEE Robotics Autom. Lett., 2021)

Development of a Basic Educational Kit for Robotic System with Deep Neural Networks. - Momomi Kanamura; Kanata Suzuki; Yuki Suga; Tetsuya Ogata (Sensors, 2021)

Buttoning Task with a Dual-Arm Robot: An Exploratory Study on a Marker-based Algorithmic Method and Marker-less Machine Learning Methods. - Wakana Fujii; Kanata Suzuki; Tomoki Ando; Ai Tateishi; Hiroki Mori; Tetsuya Ogata (SII, 2022)

Three approaches to facilitate invariant neurons and generalization to out-of-distribution orientations and illuminations. - Akira Sakai; Taro Sunagawa; Spandan Madan; Kanata Suzuki; Takashi Katoh; Hiromichi Kobashi; Hanspeter Pfister; Pawan Sinha; Xavier Boix; Tomotake Sasaki (Neural Networks, 2022)

Learning Bidirectional Translation Between Descriptions and Actions With Small Paired Data. - Minori Toyoda; Kanata Suzuki; Yoshihiko Hayashi; Tetsuya Ogata (IEEE Robotics Autom. Lett., 2022)

Multi-Timestep-Ahead Prediction with Mixture of Experts for Embodied Question Answering. - Kanata Suzuki; Yuya Kamiwano; Naoya Chiba; Hiroki Mori; Tetsuya Ogata (ICANN (6), 2023)

Machine Learning Approach for Frozen Tuna Freshness Inspection Using Low-Frequency A-Mode Ultrasound. - Akira Sakai; Masafumi Yagi; Suguru Yasutomi; Kazuki Mizuno; Kanata Suzuki; Keiichi Goto (IEEE Access, 2023)

Deep Predictive Learning : Motion Learning Concept inspired by Cognitive Robotics. - Kanata Suzuki; Hiroshi Ito; Tatsuro Yamada; Kei Kase; Tetsuya Ogata (CoRR, 2023)

Realtime Motion Generation with Active Perception Using Attention Mechanism for Cooking Robot. - Namiko Saito; Mayu Hiramoto; Ayuna Kubo; Kanata Suzuki; Hiroshi Ito; Shigeki Sugano; Tetsuya Ogata (CoRR, 2023)

Sensorimotor Attention and Language-based Regressions in Shared Latent Variables for Integrating Robot Motion Learning and LLM. - Kanata Suzuki; Tetsuya Ogata (IROS, 2024)

Interactively Robot Action Planning with Uncertainty Analysis and Active Questioning by Large Language Model. - Kazuki Hori; Kanata Suzuki; Tetsuya Ogata (SII, 2024)