Tomotake Sasaki

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 27

Top Topics

Fine Grained Categorization

Reinforcement Learning

Top Venues

Nat. Mach. Intell.

Publications

Amir Rahimi, Vanessa D'Amario, Moyuru Yamada, Kentaro Takemoto, Tomotake Sasaki, Xavier Boix
D3: Data Diversity Design for Systematic Generalization in Visual Question Answering. Trans. Mach. Learn. Res. 2024 (2024)
Kentaro Takemoto, Moyuru Yamada, Tomotake Sasaki, Hisanao Akima
HICO-DET-SG and V-COCO-SG: New Data Splits to Evaluate Systematic Generalization in Human-Object Interaction Detection. CoRR (2023)
Anirban Sarkar, Matthew Groth, Ian Mason, Tomotake Sasaki, Xavier Boix
Deephys: Deep Electrophysiology, Debugging Neural Networks under Distribution Shifts. CoRR (2023)
Amir Rahimi, Vanessa D'Amario, Moyuru Yamada, Kentaro Takemoto, Tomotake Sasaki, Xavier Boix
D3: Data Diversity Design for Systematic Generalization in Visual Question Answering. CoRR (2023)
Ian Mason, Anirban Sarkar, Tomotake Sasaki, Xavier Boix
Modularity Trumps Invariance for Compositional Robustness. CoRR (2023)
Spandan Madan, Timothy Henry, Jamell Dozier, Helen Ho, Nishchal Bhandari, Tomotake Sasaki, Frédo Durand, Hanspeter Pfister, Xavier Boix
When and how convolutional neural networks generalize to out-of-distribution category-viewpoint combinations. Nat. Mach. Intell. 4 (2) (2022)
Akira Sakai, Taro Sunagawa, Spandan Madan, Kanata Suzuki, Takashi Katoh, Hiromichi Kobashi, Hanspeter Pfister, Pawan Sinha, Xavier Boix, Tomotake Sasaki
Three approaches to facilitate invariant neurons and generalization to out-of-distribution orientations and illuminations. Neural Networks 155 (2022)
Vanessa D'Amario, Sanjana Srivastava, Tomotake Sasaki, Xavier Boix
The Data Efficiency of Deep Learning Is Degraded by Unnecessary Input Dimensions. Frontiers Comput. Neurosci. 16 (2022)
Yoshihiro Okawa, Tomotake Sasaki, Hitoshi Yanami, Toru Namerikawa
Safe Exploration Method for Reinforcement Learning Under Existence of Disturbance. ECML/PKDD (4) (2022)
Yoshihiro Okawa, Tomotake Sasaki, Hitoshi Yanami, Toru Namerikawa
Safe Exploration Method for Reinforcement Learning under Existence of Disturbance. CoRR (2022)
Moyuru Yamada, Vanessa D'Amario, Kentaro Takemoto, Xavier Boix, Tomotake Sasaki
Transformer Module Networks for Systematic Generalization in Visual Question Answering. CoRR (2022)
Kimberly Villalobos, Vilim Stih, Amineh Ahmadinejad, Shobhita Sundaram, Jamell Dozier, Andrew Francl, Frederico Azevedo, Tomotake Sasaki, Xavier Boix
Do Neural Networks for Segmentation Understand Insideness? CoRR (2022)
Yoshihiro Okawa, Tomotake Sasaki, Hidenao Iwane
Automatic Exploration Process Adjustment for Safe Reinforcement Learning with Joint Chance Constraint Satisfaction. CoRR (2021)
Avi Cooper, Xavier Boix, Daniel Harari, Spandan Madan, Hanspeter Pfister, Tomotake Sasaki, Pawan Sinha
To Which Out-Of-Distribution Object Orientations Are DNNs Capable of Generalizing? CoRR (2021)
Kanata Suzuki, Taro Sunagawa, Tomotake Sasaki, Takashi Katoh
Annotation Cost Reduction of Stream-based Active Learning by Automated Weak Labeling using a Robot Arm. IROS (2021)
Spandan Madan, Tomotake Sasaki, Tzu-Mao Li, Xavier Boix, Hanspeter Pfister
Small in-distribution changes in 3D perspective and lighting fool both CNNs and Transformers. CoRR (2021)
Vanessa D'Amario, Tomotake Sasaki, Xavier Boix
How Modular should Neural Module Networks Be for Systematic Generalization? NeurIPS (2021)
Shobhita Sundaram, Darius Sinha, Matthew Groth, Tomotake Sasaki, Xavier Boix
Symmetry Perception by Deep Networks: Inadequacy of Feed-Forward Architectures and Improvements with Recurrent Connections. CoRR (2021)
Yuka Masumoto, Yoshihiro Okawa, Tomotake Sasaki, Yutaka Hori
Model-free two-step design for improving transient learning performance in nonlinear optimal regulator problems. CoRR (2021)
Kimberly Villalobos, Vilim Stih, Amineh Ahmadinejad, Shobhita Sundaram, Jamell Dozier, Andrew Francl, Frederico Azevedo, Tomotake Sasaki, Xavier Boix
Do Neural Networks for Segmentation Understand Insideness? Neural Comput. 33 (9) (2021)
Vanessa D'Amario, Tomotake Sasaki, Xavier Boix
How Modular Should Neural Module Networks Be for Systematic Generalization? CoRR (2021)
Kanata Suzuki, Taro Sunagawa, Tomotake Sasaki, Takashi Katoh
Annotation Cost Reduction of Stream-based Active Learning by Automated Weak Labeling using a Robot Arm. CoRR (2021)
Akira Sakai, Taro Sunagawa, Spandan Madan, Kanata Suzuki, Takashi Katoh, Hiromichi Kobashi, Hanspeter Pfister, Pawan Sinha, Xavier Boix, Tomotake Sasaki
Three approaches to facilitate DNN generalization to objects in out-of-distribution orientations and illuminations: late-stopping, tuning batch normalization and invariance loss. CoRR (2021)
Vanessa D'Amario, Sanjana Srivastava, Tomotake Sasaki, Xavier Boix
The Foes of Neural Network's Data Efficiency Among Unnecessary Input Dimensions. CoRR (2021)
Keizo Kato, Jing Zhou, Tomotake Sasaki, Akira Nakagawa
Rate-distortion optimization guided autoencoder for isometric embedding in Euclidean latent space. ICML (2020)
Spandan Madan, Timothy Henry, Jamell Dozier, Helen Ho, Nishchal Bhandari, Tomotake Sasaki, Frédo Durand, Hanspeter Pfister, Xavier Boix
On the Capability of Neural Networks to Generalize to Unseen Category-Pose Combinations. CoRR (2020)
Yoshihiro Okawa, Tomotake Sasaki, Hidenao Iwane
Control Approach Combining Reinforcement Learning and Model-Based Control. ASCC (2019)
Hitoshi Yanami, Tomotake Sasaki, Junji Kaneko, Shinji Hara, Yafei Wang, Satoshi Moriyama, Hidenao Iwane
State-dependent virtual hierarchization of batteries for realizing a glocal control in energy network systems and its application to peak power reduction in office. ASCC (2015)
Tomotake Sasaki, Shinji Hara, Koji Tsumura
Accessibility Analysis for Controlled Quantum Systems under Continuous Quantum Measurement. CCA (2010)