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Deep Learning Detection of GPS Spoofing

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Deep Learning Theory Through the Lens of Diagonal Linear Networks

Scott William Pesme

In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

2

-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

EPFL2024

Deep Learning Detection of GPS Spoofing

Graph Chatbot

Chattez avec Graph Search

Deep Learning Theory Through the Lens of Diagonal Linear Networks

On the number of regions of piecewise linear neural networks

Random matrix methods for high-dimensional machine learning models

Machine Learning for Modeling Stock Returns

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Error assessment of an adaptive finite elements-neural networks method for an elliptic parametric PDE

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Machine Learning for Modeling Stock Returns

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Random matrix methods for high-dimensional machine learning models

On the number of regions of piecewise linear neural networks

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Error assessment of an adaptive finite elements-neural networks method for an elliptic parametric PDE

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning