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Neural tensor contractions and the expressive power of deep neural quantum states

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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

Neural tensor contractions and the expressive power of deep neural quantum states

Graph Chatbot

Chattez avec Graph Search

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Random matrix methods for high-dimensional machine learning models

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

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

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

On the number of regions of piecewise linear neural networks

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

Topics in statistical physics of high-dimensional machine learning

Generalization of Scaled Deep ResNets in the Mean-Field Regime

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

On the number of regions of piecewise linear neural networks

Random matrix methods for high-dimensional machine learning models

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

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

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

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

Topics in statistical physics of high-dimensional machine learning