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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

Réseau de neurones à propagation avant

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

Generalization of Scaled Deep ResNets in the Mean-Field Regime

On the number of regions of piecewise linear neural networks

Explainable Face Verification via Feature-Guided Gradient Backpropagation

Deep Learning Theory Through the Lens of Diagonal Linear Networks

33.3 MiBMI: A 192/512-Channel 2.46mm² Miniaturized Brain-Machine Interface Chipset Enabling 31-Class Brain-to-Text Conversion Through Distinctive Neural Codes

Random matrix methods for high-dimensional machine learning models

MaskCLR: Attention-Guided Contrastive Learning for Robust Action Representation Learning

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

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

Generalization of Scaled Deep ResNets in the Mean-Field Regime

MaskCLR: Attention-Guided Contrastive Learning for Robust Action Representation Learning

Deep Learning Theory Through the Lens of Diagonal Linear Networks

33.3 MiBMI: A 192/512-Channel 2.46mm² Miniaturized Brain-Machine Interface Chipset Enabling 31-Class Brain-to-Text Conversion Through Distinctive Neural Codes

On the number of regions of piecewise linear neural networks

Random matrix methods for high-dimensional machine learning models

Explainable Face Verification via Feature-Guided Gradient Backpropagation

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

Topics in statistical physics of high-dimensional machine learning