research
∙
05/25/2023
An Experimental Investigation into the Evaluation of Explainability Methods
EXplainable Artificial Intelligence (XAI) aims to help users to grasp th...
share
research
∙
04/18/2023
SO(2) and O(2) Equivariance in Image Recognition with Bessel-Convolutional Neural Networks
For many years, it has been shown how much exploiting equivariances can ...
research
∙
02/10/2023
Industrial and Medical Anomaly Detection Through Cycle-Consistent Adversarial Networks
In this study, a new Anomaly Detection (AD) approach for real-world imag...
research
∙
11/25/2022
Composite Score for Anomaly Detection in Imbalanced Real-World Industrial Dataset
In recent years, the industrial sector has evolved towards its fourth re...
research
∙
05/19/2021
DumbleDR: Predicting User Preferences of Dimensionality Reduction Projection Quality
A plethora of dimensionality reduction techniques have emerged over the ...
research
∙
07/10/2020
Impact of Legal Requirements on Explainability in Machine Learning
The requirements on explainability imposed by European laws and their im...
research
∙
05/14/2020
Ethical Adversaries: Towards Mitigating Unfairness with Adversarial Machine Learning
Machine learning is being integrated into a growing number of critical s...
research
∙
11/18/2016
