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05/19/2023
What You Hear Is What You See: Audio Quality Metrics From Image Quality Metrics
In this study, we investigate the feasibility of utilizing state-of-the-...
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03/17/2023
Disentangling the Link Between Image Statistics and Human Perception
In the 1950s Horace Barlow and Fred Attneave suggested a connection betw...
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01/19/2023
Identification, explanation and clinical evaluation of hospital patient subtypes
We present a pipeline in which unsupervised machine learning techniques ...
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09/08/2022
What and How of Machine Learning Transparency: Building Bespoke Explainability Tools with Interoperable Algorithmic Components
Explainability techniques for data-driven predictive models based on art...
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09/08/2022
FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems
Predictive systems, in particular machine learning algorithms, can take ...
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08/08/2022
Sampling Based On Natural Image Statistics Improves Local Surrogate Explainers
Many problems in computer vision have recently been tackled using models...
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06/08/2022
Orthonormal Convolutions for the Rotation Based Iterative Gaussianization
In this paper we elaborate an extension of rotation-based iterative Gaus...
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06/08/2021
On the relation between statistical learning and perceptual distances
It has been demonstrated many times that the behavior of the human visua...
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02/22/2021
Explainers in the Wild: Making Surrogate Explainers Robust to Distortions through Perception
Explaining the decisions of models is becoming pervasive in the image pr...
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10/29/2019
bLIMEy: Surrogate Prediction Explanations Beyond LIME
Surrogate explainers of black-box machine learning predictions are of pa...
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10/28/2019
PerceptNet: A Human Visual System Inspired Neural Network for Estimating Perceptual Distance
Traditionally, the vision community has devised algorithms to estimate t...
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08/09/2019
