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07/12/2023
Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution
The ubiquitous and demonstrably suboptimal choice of resizing images to ...
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06/07/2023
Don't trust your eyes: on the (un)reliability of feature visualizations
How do neural networks extract patterns from pixels? Feature visualizati...
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05/26/2023
Are Deep Neural Networks Adequate Behavioural Models of Human Visual Perception?
Deep neural networks (DNNs) are machine learning algorithms that have re...
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06/29/2022
Beyond neural scaling laws: beating power law scaling via data pruning
Widely observed neural scaling laws, in which error falls off as a power...
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05/20/2022
The developmental trajectory of object recognition robustness: children are like small adults but unlike big deep neural networks
In laboratory object recognition tasks based on undistorted photographs,...
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10/12/2021
Trivial or impossible – dichotomous data difficulty masks model differences (on ImageNet and beyond)
"The power of a generalization system follows directly from its biases" ...
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06/23/2021
How Well do Feature Visualizations Support Causal Understanding of CNN Activations?
One widely used approach towards understanding the inner workings of dee...
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06/14/2021
Partial success in closing the gap between human and machine vision
A few years ago, the first CNN surpassed human performance on ImageNet. ...
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10/23/2020
Exemplary Natural Images Explain CNN Activations Better than Feature Visualizations
Feature visualizations such as synthetic maximally activating images are...
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10/16/2020
On the surprising similarities between supervised and self-supervised models
How do humans learn to acquire a powerful, flexible and robust represent...
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06/30/2020
Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans by measuring error consistency
A central problem in cognitive science and behavioural neuroscience as w...
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04/16/2020
Shortcut Learning in Deep Neural Networks
Deep learning has triggered the current rise of artificial intelligence ...
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07/17/2019
Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming
The ability to detect objects regardless of image distortions or weather...
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11/29/2018
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
Convolutional Neural Networks (CNNs) are commonly thought to recognise o...
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08/27/2018
Generalisation in humans and deep neural networks
We compare the robustness of humans and current convolutional deep neura...
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06/21/2017
