324 citations · 1.4k across the 135 of their papers we have counts for
6 papers · 1 filter
A Rate-Distortion Framework for Explaining Black-box Model Decisions
Stefan Kolek, Duc Anh Nguyen, Ron Levie +2
We present the Rate-Distortion Explanation (RDE) framework, a mathematically well-founded method for explaining black-box model decisions. The framework is based on perturbations o…
Cartoon Explanations of Image Classifiers
Stefan Kolek, Duc Anh Nguyen, Ron Levie +2
We present CartoonX (Cartoon Explanation), a novel model-agnostic explanation method tailored towards image classifiers and based on the rate-distortion explanation (RDE) framework…
Transferability of Graph Neural Networks: an Extended Graphon Approach
Sohir Maskey, Ron Levie, Gitta Kutyniok
We study spectral graph convolutional neural networks (GCNNs), where filters are defined as continuous functions of the graph shift operator (GSO) through functional calculus. A sp…
Deep Microlocal Reconstruction for Limited-Angle Tomography
Héctor Andrade-Loarca, Gitta Kutyniok, Ozan Öktem +1
We present a deep learning-based algorithm to jointly solve a reconstruction problem and a wavefront set extraction problem in tomographic imaging. The algorithm is based on a rece…
Real-time Outdoor Localization Using Radio Maps: A Deep Learning Approach
Çağkan Yapar, Ron Levie, Gitta Kutyniok +1
Global Navigation Satellite Systems typically perform poorly in urban environments, where the likelihood of line-of-sight conditions between devices and satellites is low. Therefor…
The Modern Mathematics of Deep Learning
Julius Berner, Philipp Grohs, Gitta Kutyniok +1
We describe the new field of mathematical analysis of deep learning. This field emerged around a list of research questions that were not answered within the classical framework of…