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09/15/2023
D3: Data Diversity Design for Systematic Generalization in Visual Question Answering
Systematic generalization is a crucial aspect of intelligence, which ref...
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06/15/2023
Modularity Trumps Invariance for Compositional Robustness
By default neural networks are not robust to changes in data distributio...
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05/17/2023
HICO-DET-SG and V-COCO-SG: New Data Splits to Evaluate Systematic Generalization in Human-Object Interaction Detection
Human-Object Interaction (HOI) detection is a task to predict interactio...
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03/17/2023
Deephys: Deep Electrophysiology, Debugging Neural Networks under Distribution Shifts
Deep Neural Networks (DNNs) often fail in out-of-distribution scenarios....
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09/30/2022
Safe Exploration Method for Reinforcement Learning under Existence of Disturbance
Recent rapid developments in reinforcement learning algorithms have been...
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01/27/2022
Transformer Module Networks for Systematic Generalization in Visual Question Answering
Transformer-based models achieve great performance on Visual Question An...
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01/25/2022
Do Neural Networks for Segmentation Understand Insideness?
The insideness problem is an aspect of image segmentation that consists ...
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12/08/2021
Symmetry Perception by Deep Networks: Inadequacy of Feed-Forward Architectures and Improvements with Recurrent Connections
Symmetry is omnipresent in nature and perceived by the visual system of ...
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10/30/2021
Three approaches to facilitate DNN generalization to objects in out-of-distribution orientations and illuminations: late-stopping, tuning batch normalization and invariance los
The training data distribution is often biased towards objects in certai...
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10/03/2021
Annotation Cost Reduction of Stream-based Active Learning by Automated Weak Labeling using a Robot Arm
Stream-based active learning (AL) is an efficient training data collecti...
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07/13/2021
The Foes of Neural Network's Data Efficiency Among Unnecessary Input Dimensions
Datasets often contain input dimensions that are unnecessary to predict ...
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06/30/2021
Small in-distribution changes in 3D perspective and lighting fool both CNNs and Transformers
Neural networks are susceptible to small transformations including 2D ro...
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06/15/2021
How Modular Should Neural Module Networks Be for Systematic Generalization?
Neural Module Networks (NMNs) aim at Visual Question Answering (VQA) via...
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03/05/2021
Model-free two-step design for improving transient learning performance in nonlinear optimal regulator problems
Reinforcement learning (RL) provides a model-free approach to designing ...
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03/05/2021
Automatic Exploration Process Adjustment for Safe Reinforcement Learning with Joint Chance Constraint Satisfaction
In reinforcement learning (RL) algorithms, exploratory control inputs ar...
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07/15/2020
