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08/16/2023
Expressivity of Spiking Neural Networks
This article studies the expressive power of spiking neural networks whe...
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08/03/2023
PoissonNet: Resolution-Agnostic 3D Shape Reconstruction using Fourier Neural Operators
We introduce PoissonNet, an architecture for shape reconstruction that a...
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07/05/2023
Sumformer: Universal Approximation for Efficient Transformers
Natural language processing (NLP) made an impressive jump with the intro...
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07/03/2023
Reliable AI: Does the Next Generation Require Quantum Computing?
In this survey, we aim to explore the fundamental question of whether th...
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06/15/2023
On the Interplay of Subset Selection and Informed Graph Neural Networks
Machine learning techniques paired with the availability of massive data...
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06/10/2023
Learning optimal controllers: a dynamical motion primitive approach
Real-time computation of optimal control is a challenging problem and, t...
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05/25/2023
Neural (Tangent Kernel) Collapse
This work bridges two important concepts: the Neural Tangent Kernel (NTK...
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05/22/2023
A Fractional Graph Laplacian Approach to Oversmoothing
Graph neural networks (GNNs) have shown state-of-the-art performances in...
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01/26/2023
Graph Scattering beyond Wavelet Shackles
This work develops a flexible and mathematically sound framework for the...
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01/15/2023
Computability of Optimizers
Optimization problems are a staple of today's scientific and technical l...
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12/06/2022
Non-Computability of the Pseudoinverse on Digital Computers
The pseudoinverse of a matrix, a generalized notion of the inverse, is o...
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12/01/2022
Complexity Blowup for Solutions of the Laplace and the Diffusion Equation
In this paper, we investigate the computational complexity of solutions ...
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11/22/2022
Explaining Image Classifiers with Multiscale Directional Image Representation
Image classifiers are known to be difficult to interpret and therefore r...
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11/18/2022
Dataset of Pathloss and ToA Radio Maps With Localization Application
In this article, we present a collection of radio map datasets in dense ...
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10/15/2022
Well-definedness of Physical Law Learning: The Uniqueness Problem
Physical law learning is the ambiguous attempt at automating the derivat...
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10/15/2022
Unveiling the Sampling Density in Non-Uniform Geometric Graphs
A powerful framework for studying graphs is to consider them as geometri...
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06/11/2022
Memorization-Dilation: Modeling Neural Collapse Under Noise
The notion of neural collapse refers to several emergent phenomena that ...
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05/30/2022
OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs
This work provides the first theoretical study on the ability of graph M...
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03/16/2022
The Mathematics of Artificial Intelligence
We currently witness the spectacular success of artificial intelligence ...
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02/28/2022
Limitations of Deep Learning for Inverse Problems on Digital Hardware
Deep neural networks have seen tremendous success over the last years. S...
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02/01/2022
LocUNet: Fast Urban Positioning Using Radio Maps and Deep Learning
This paper deals with the problem of localization in a cellular network ...
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02/01/2022
Stability and Generalization Capabilities of Message Passing Graph Neural Networks
Message passing neural networks (MPNN) have seen a steep rise in popular...
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02/01/2022
Neural Tangent Kernel Beyond the Infinite-Width Limit: Effects of Depth and Initialization
Neural Tangent Kernel (NTK) is widely used to analyze overparametrized n...
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10/12/2021
A Rate-Distortion Framework for Explaining Black-box Model Decisions
We present the Rate-Distortion Explanation (RDE) framework, a mathematic...
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10/07/2021
Cartoon Explanations of Image Classifiers
We present CartoonX (Cartoon Explanation), a novel model-agnostic explan...
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09/21/2021
Transferability of Graph Neural Networks: an Extended Graphon Approach
We study spectral graph convolutional neural networks (GCNNs), where fil...
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08/12/2021
Deep Microlocal Reconstruction for Limited-Angle Tomography
We present a deep learning-based algorithm to jointly solve a reconstruc...
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06/23/2021
Real-time Outdoor Localization Using Radio Maps: A Deep Learning Approach
This paper deals with the problem of localization in a cellular network ...
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05/09/2021
The Modern Mathematics of Deep Learning
We describe the new field of mathematical analysis of deep learning. Thi...
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12/08/2020
Analyzing Finite Neural Networks: Can We Trust Neural Tangent Kernel Theory?
Neural Tangent Kernel (NTK) theory is widely used to study the dynamics ...
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11/03/2020
Quasi Monte Carlo Time-Frequency Analysis
We study signal processing tasks in which the signal is mapped via some ...
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07/09/2020
Expressivity of Deep Neural Networks
In this review paper, we give a comprehensive overview of the large vari...
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07/01/2020
In-Distribution Interpretability for Challenging Modalities
It is widely recognized that the predictions of deep neural networks are...
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07/01/2020
The Restricted Isometry of ReLU Networks: Generalization through Norm Concentration
While regression tasks aim at interpolating a relation on the entire inp...
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06/09/2020
Real-time Localization Using Radio Maps
This paper deals with the problem of localization in a cellular network ...
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06/08/2020
tfShearlab: The TensorFlow Digital Shearlet Transform for Deep Learning
The shearlet transform from applied harmonic analysis is currently the s...
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04/25/2020
Numerical Solution of the Parametric Diffusion Equation by Deep Neural Networks
We perform a comprehensive numerical study of the effect of approximatio...
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03/25/2020
Interval Neural Networks: Uncertainty Scores
We propose a fast, non-Bayesian method for producing uncertainty scores ...
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11/27/2019
Shearlets as Feature Extractor for Semantic Edge Detection: The Model-Based and Data-Driven Realm
Semantic edge detection has recently gained a lot of attention as an ima...
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11/17/2019
RadioUNet: Fast Radio Map Estimation with Convolutional Neural Networks
In this paper we propose a highly efficient and very accurate method for...
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07/30/2019
Transferability of Spectral Graph Convolutional Neural Networks
This paper focuses on spectral graph convolutional neural networks (Conv...
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05/27/2019
A Rate-Distortion Framework for Explaining Neural Network Decisions
We formalise the widespread idea of interpreting neural network decision...
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05/22/2019
The Computational Complexity of Understanding Network Decisions
For a Boolean function Φ{0,1}^d→{0,1} and an assignment to its variables...
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05/03/2019
Approximation spaces of deep neural networks
We study the expressivity of deep neural networks. Measuring a network's...
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03/31/2019
A Theoretical Analysis of Deep Neural Networks and Parametric PDEs
We derive upper bounds on the complexity of ReLU neural networks approxi...
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02/21/2019
Error bounds for approximations with deep ReLU neural networks in W^s,p norms
We analyze approximation rates of deep ReLU neural networks for Sobolev-...
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01/29/2019
On the Transferability of Spectral Graph Filters
This paper focuses on spectral filters on graphs, namely filters defined...
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01/17/2019
The Oracle of DLphi
We present a novel technique based on deep learning and set theory which...
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01/05/2019
Extraction of digital wavefront sets using applied harmonic analysis and deep neural networks
Microlocal analysis provides deep insight into singularity structures an...
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08/20/2018
