Publication

Hamiltonian Deep Neural Networks Guaranteeing Non-Vanishing Gradients by Design

Publications associées (112)

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

Hamiltonian Deep Neural Networks Guaranteeing Non-Vanishing Gradients by Design

Graph Chatbot

Chattez avec Graph Search

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Deep Learning Theory Through the Lens of Diagonal Linear Networks

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

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs

Explainable Face Verification via Feature-Guided Gradient Backpropagation

Deep Learning Generalization with Limited and Noisy Labels

From Kernel Methods to Neural Networks: A Unifying Variational Formulation

Supervised learning and inference of spiking neural networks with temporal coding

Benign Overfitting in Deep Neural Networks under Lazy Training

Predicting nonlinear optical scattering with physics-driven neural networks

Explainable Face Verification via Feature-Guided Gradient Backpropagation

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Supervised learning and inference of spiking neural networks with temporal coding

From Kernel Methods to Neural Networks: A Unifying Variational Formulation

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Deep Learning Generalization with Limited and Noisy Labels

Benign Overfitting in Deep Neural Networks under Lazy Training

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

Predicting nonlinear optical scattering with physics-driven neural networks

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs