Publications associées à Prime manifold

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.

Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances

Wulfram Gerstner, Clément Hongler, Johanni Michael Brea, Francesco Spadaro, Berfin Simsek, Arthur Jacot

We study how permutation symmetries in overparameterized multi-layer neural networks generate `symmetry-induced' critical points. Assuming a network with

L

layers of minimal widths

r_1^*, \ldots, r_{L-1}^*

reaches a zero-loss minimum at $ r_1^*! \c ...

2021

Prime manifold

Graph Chatbot

Chattez avec Graph Search

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

OSLO: On-the-Sphere Learning for Omnidirectional Images and Its Application to 360-Degree Image Compression

Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances

Shrinking Scale Equidistribution for Monochromatic Random Waves on Compact Manifolds

Dynamical Reduced Basis Methods for Hamiltonian Systems

Learning Smooth Pattern Transformation Manifolds

Learning Pattern Transformation Manifolds for Classification

Discretization of Parametrizable Signal Manifolds

Optimal image alignment with random projections of manifolds: algorithm and geometric analysis

A NUMERICAL MANIFOLD METHOD FOR PLANE MICROPOLAR ELASTICITY

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

OSLO: On-the-Sphere Learning for Omnidirectional Images and Its Application to 360-Degree Image Compression

Shrinking Scale Equidistribution for Monochromatic Random Waves on Compact Manifolds

Dynamical Reduced Basis Methods for Hamiltonian Systems

Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances

Optimal image alignment with random projections of manifolds: algorithm and geometric analysis

A NUMERICAL MANIFOLD METHOD FOR PLANE MICROPOLAR ELASTICITY

Learning Pattern Transformation Manifolds for Classification

Discretization of Parametrizable Signal Manifolds

Learning Smooth Pattern Transformation Manifolds