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06/19/2023
B-cos Alignment for Inherently Interpretable CNNs and Vision Transformers
We present a new direction for increasing the interpretability of deep n...
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03/23/2023
Temperature Schedules for Self-Supervised Contrastive Methods on Long-Tail Data
Most approaches for self-supervised learning (SSL) are optimised on cura...
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03/21/2023
Using Explanations to Guide Models
Deep neural networks are highly performant, but might base their decisio...
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03/21/2023
Better Understanding Differences in Attribution Methods via Systematic Evaluations
Deep neural networks are very successful on many vision tasks, but hard ...
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01/20/2023
Holistically Explainable Vision Transformers
Transformers increasingly dominate the machine learning landscape across...
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05/20/2022
Towards Better Understanding Attribution Methods
Deep neural networks are very successful on many vision tasks, but hard ...
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05/20/2022
B-cos Networks: Alignment is All We Need for Interpretability
We present a new direction for increasing the interpretability of deep n...
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09/27/2021
Optimising for Interpretability: Convolutional Dynamic Alignment Networks
We introduce a new family of neural network models called Convolutional ...
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03/31/2021
