Publication

Controlling the Complexity and Lipschitz Constant improves Polynomial Nets

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search

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

Controlling the Complexity and Lipschitz Constant improves Polynomial Nets

Graph Chatbot

Chattez avec Graph Search

Intraday solar irradiance forecasting using public cameras

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

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

Random matrix methods for high-dimensional machine learning models

InterpretCC: Intrinsic User-Centric Interpretability through Global Mixture of Experts

Reduced Training Data for Laser Ultrasound Signal Interpretation by 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

Generalization of Scaled Deep ResNets in the Mean-Field Regime

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

Intraday solar irradiance forecasting using public cameras

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

Random matrix methods for high-dimensional machine learning models

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

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

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

InterpretCC: Intrinsic User-Centric Interpretability through Global Mixture of Experts

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Generalization of Scaled Deep ResNets in the Mean-Field Regime