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Fast and Provable ADMM for Learning with Generative Priors

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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

Fast and Provable ADMM for Learning with Generative Priors

Graph Chatbot

Chattez avec Graph Search

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

Topics in statistical physics of high-dimensional machine learning

Random matrix methods for high-dimensional machine learning models

Deep Learning Theory Through the Lens of Diagonal Linear Networks

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

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

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Intraday solar irradiance forecasting using public cameras

Generalization of Scaled Deep ResNets in the Mean-Field Regime

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

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

Intraday solar irradiance forecasting using public cameras

Random matrix methods for high-dimensional machine learning models

Deep Learning Theory Through the Lens of Diagonal Linear Networks

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

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Generalization of Scaled Deep ResNets in the Mean-Field Regime