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Empirical study of the topology and geometry of deep networks

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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

Empirical study of the topology and geometry of deep networks

Graph Chatbot

Chat with Graph Search

Understanding generalization and robustness in modern deep learning

Random matrix methods for high-dimensional machine learning models

Residual-based attention in physics-informed neural networks

Robust NAS under adversarial training: benchmark, theory, and beyond

Intraday solar irradiance forecasting using public cameras

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

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

Deep Learning Theory Through the Lens of Diagonal Linear Networks

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

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Understanding generalization and robustness in modern deep learning

Random matrix methods for high-dimensional machine learning models

Residual-based attention in physics-informed neural networks

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

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

Deep Learning Theory Through the Lens of Diagonal Linear Networks

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

Robust NAS under adversarial training: benchmark, theory, and beyond

Intraday solar irradiance forecasting using public cameras

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms