Tomotake Sasaki

Orcid: 0000-0002-3376-2779

According to our database1, Tomotake Sasaki authored at least 24 papers between 2010 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2023
D3: Data Diversity Design for Systematic Generalization in Visual Question Answering.
CoRR, 2023

Modularity Trumps Invariance for Compositional Robustness.
CoRR, 2023

HICO-DET-SG and V-COCO-SG: New Data Splits for Evaluating the Systematic Generalization Performance of Human-Object Interaction Detection Models.
CoRR, 2023

Deephys: Deep Electrophysiology, Debugging Neural Networks under Distribution Shifts.
CoRR, 2023

2022
Three approaches to facilitate invariant neurons and generalization to out-of-distribution orientations and illuminations.
Neural Networks, 2022

When and how convolutional neural networks generalize to out-of-distribution category-viewpoint combinations.
Nat. Mach. Intell., 2022

The Data Efficiency of Deep Learning Is Degraded by Unnecessary Input Dimensions.
Frontiers Comput. Neurosci., 2022

Transformer Module Networks for Systematic Generalization in Visual Question Answering.
CoRR, 2022

Safe Exploration Method for Reinforcement Learning Under Existence of Disturbance.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

2021
Do Neural Networks for Segmentation Understand Insideness?
Neural Comput., 2021

Symmetry Perception by Deep Networks: Inadequacy of Feed-Forward Architectures and Improvements with Recurrent Connections.
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.
CoRR, 2021

To Which Out-Of-Distribution Object Orientations Are DNNs Capable of Generalizing?
CoRR, 2021

The Foes of Neural Network's Data Efficiency Among Unnecessary Input Dimensions.
CoRR, 2021

Small in-distribution changes in 3D perspective and lighting fool both CNNs and Transformers.
CoRR, 2021

Model-free two-step design for improving transient learning performance in nonlinear optimal regulator problems.
CoRR, 2021

Automatic Exploration Process Adjustment for Safe Reinforcement Learning with Joint Chance Constraint Satisfaction.
CoRR, 2021

How Modular should Neural Module Networks Be for Systematic Generalization?
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Annotation Cost Reduction of Stream-based Active Learning by Automated Weak Labeling using a Robot Arm.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

2020
On the Capability of Neural Networks to Generalize to Unseen Category-Pose Combinations.
CoRR, 2020

Rate-distortion optimization guided autoencoder for isometric embedding in Euclidean latent space.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Control Approach Combining Reinforcement Learning and Model-Based Control.
Proceedings of the 12th Asian Control Conference, 2019

2015
State-dependent virtual hierarchization of batteries for realizing a glocal control in energy network systems and its application to peak power reduction in office.
Proceedings of the 10th Asian Control Conference, 2015

2010
Accessibility Analysis for Controlled Quantum Systems under Continuous Quantum Measurement.
Proceedings of the IEEE International Conference on Control Applications, 2010


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