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Networks of Mixed Canonic-Dissipative Systems and Dynamic Hebbian Learning

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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

Networks of Mixed Canonic-Dissipative Systems and Dynamic Hebbian Learning

Graph Chatbot

Chattez avec Graph Search

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Fear learning induces synaptic potentiation between engram neurons in the rat lateral amygdala

Topics in statistical physics of high-dimensional machine learning

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Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

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

Random matrix methods for high-dimensional machine learning models

Towards improving full-length ribosome density prediction by bridging sequence and graph-based representations

Deep Learning Theory Through the Lens of Diagonal Linear Networks

A Tutorial-Cum-Survey on Percolation Theory With Applications in Large-Scale Wireless Networks

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Fear learning induces synaptic potentiation between engram neurons in the rat lateral amygdala

Topics in statistical physics of high-dimensional machine learning

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Random matrix methods for high-dimensional machine learning models

Towards improving full-length ribosome density prediction by bridging sequence and graph-based representations

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

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

Deep Learning Theory Through the Lens of Diagonal Linear Networks

A Tutorial-Cum-Survey on Percolation Theory With Applications in Large-Scale Wireless Networks