Accessibility Analysis for Controlled Quantum Systems under Continuous Quantum Measurement. - Tomotake Sasaki; Shinji Hara; Koji Tsumura (CCA, 2010)

State-dependent virtual hierarchization of batteries for realizing a glocal control in energy network systems and its application to peak power reduction in office. - Hitoshi Yanami; Tomotake Sasaki; Junji Kaneko; Shinji Hara; Yafei Wang 002; Satoshi Moriyama; Hidenao Iwane (ASCC, 2015)

Control Approach Combining Reinforcement Learning and Model-Based Control. - Yoshihiro Okawa; Tomotake Sasaki; Hidenao Iwane (ASCC, 2019)

Rate-distortion optimization guided autoencoder for isometric embedding in Euclidean latent space. - Keizo Kato; Jing Zhou; Tomotake Sasaki; Akira Nakagawa (ICML, 2020)

On the Capability of Neural Networks to Generalize to Unseen Category-Pose Combinations. - Spandan Madan; Timothy Henry; Jamell Dozier; Helen Ho; Nishchal Bhandari; Tomotake Sasaki; Frédo Durand; Hanspeter Pfister; Xavier Boix (CoRR, 2020)

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)

How Modular should Neural Module Networks Be for Systematic Generalization? - Vanessa D'Amario; Tomotake Sasaki; Xavier Boix (NeurIPS, 2021)

Automatic Exploration Process Adjustment for Safe Reinforcement Learning with Joint Chance Constraint Satisfaction. - Yoshihiro Okawa; Tomotake Sasaki; Hidenao Iwane (CoRR, 2021)

Model-free two-step design for improving transient learning performance in nonlinear optimal regulator problems. - Yuka Masumoto; Yoshihiro Okawa; Tomotake Sasaki; Yutaka Hori (CoRR, 2021)

Small in-distribution changes in 3D perspective and lighting fool both CNNs and Transformers. - Spandan Madan; Tomotake Sasaki; Tzu-Mao Li; Xavier Boix; Hanspeter Pfister (CoRR, 2021)

The Foes of Neural Network's Data Efficiency Among Unnecessary Input Dimensions. - Vanessa D'Amario; Sanjana Srivastava; Tomotake Sasaki; Xavier Boix (CoRR, 2021)

To Which Out-Of-Distribution Object Orientations Are DNNs Capable of Generalizing? - Avi Cooper; Xavier Boix; Daniel Harari; Spandan Madan; Hanspeter Pfister; Tomotake Sasaki; Pawan Sinha (CoRR, 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)

Symmetry Perception by Deep Networks: Inadequacy of Feed-Forward Architectures and Improvements with Recurrent Connections. - Shobhita Sundaram; Darius Sinha; Matthew Groth; Tomotake Sasaki; Xavier Boix (CoRR, 2021)

Do Neural Networks for Segmentation Understand Insideness? - Kimberly Villalobos; Vilim Stih; Amineh Ahmadinejad; Shobhita Sundaram; Jamell Dozier; Andrew Francl; Frederico Azevedo; Tomotake Sasaki; Xavier Boix (Neural Comput., 2021)

Safe Exploration Method for Reinforcement Learning Under Existence of Disturbance. - Yoshihiro Okawa; Tomotake Sasaki; Hitoshi Yanami; Toru Namerikawa (ECML/PKDD (4), 2022)

The Data Efficiency of Deep Learning Is Degraded by Unnecessary Input Dimensions. - Vanessa D'Amario; Sanjana Srivastava; Tomotake Sasaki; Xavier Boix (Frontiers Comput. Neurosci., 2022)

When and how convolutional neural networks generalize to out-of-distribution category-viewpoint combinations. - Spandan Madan; Timothy Henry; Jamell Dozier; Helen Ho; Nishchal Bhandari; Tomotake Sasaki; Frédo Durand; Hanspeter Pfister; Xavier Boix (Nat. Mach. Intell., 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)

Deephys: Deep Electrophysiology, Debugging Neural Networks under Distribution Shifts. - Anirban Sarkar; Matthew Groth; Ian Mason; Tomotake Sasaki; Xavier Boix (CoRR, 2023)

HICO-DET-SG and V-COCO-SG: New Data Splits for Evaluating the Systematic Generalization Performance of Human-Object Interaction Detection Models. - Kentaro Takemoto; Moyuru Yamada; Tomotake Sasaki; Hisanao Akima (CoRR, 2023)

Modularity Trumps Invariance for Compositional Robustness. - Ian Mason; Anirban Sarkar; Tomotake Sasaki; Xavier Boix (CoRR, 2023)

D3: Data Diversity Design for Systematic Generalization in Visual Question Answering. - Amir Rahimi; Vanessa D'Amario; Moyuru Yamada; Kentaro Takemoto; Tomotake Sasaki; Xavier Boix (Trans. Mach. Learn. Res., 2024)

Transformer Module Networks for Systematic Generalization in Visual Question Answering. - Moyuru Yamada; Vanessa D'Amario; Kentaro Takemoto; Xavier Boix; Tomotake Sasaki (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Emergent Neural Network Mechanisms for Generalization to Objects in Novel Orientations. - Avi Cooper; Daniel Harari; Tomotake Sasaki; Spandan Madan; Hanspeter Pfister; Pawan Sinha; Xavier Boix (Trans. Mach. Learn. Res., 2025)

In-distribution adversarial attacks on object recognition models using gradient-free search. - Spandan Madan; Tomotake Sasaki; Hanspeter Pfister; Tzu-Mao Li; Xavier Boix (Trans. Mach. Learn. Res., 2025)