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Matrix product states with backflow correlations

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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

Matrix product states with backflow correlations

Graph Chatbot

Chattez avec Graph Search

Random matrix methods for high-dimensional machine learning models

Gibbs sampling the posterior of neural networks

Generalization of Scaled Deep ResNets in the Mean-Field Regime

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

Sparse autoregressive neural networks for classical spin systems

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

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

Spectral Estimators for High-Dimensional Matrix Inference

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Topics in statistical physics of high-dimensional machine learning

Random matrix methods for high-dimensional machine learning models

Gibbs sampling the posterior of neural networks

Generalization of Scaled Deep ResNets in the Mean-Field Regime

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

Sparse autoregressive neural networks for classical spin systems

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

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

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Topics in statistical physics of high-dimensional machine learning

Spectral Estimators for High-Dimensional Matrix Inference