Publication

Evaluating and Interpreting Deep Convolutional Neural Networks via Non-negative Matrix Factorization

Publications associées (32)

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

Publications associées à Evaluating and Interpreting Deep Convolutional Neural Networks via Non-negative Matrix Factorization | EPFL 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

Evaluating and Interpreting Deep Convolutional Neural Networks via Non-negative Matrix Factorization

Graph Chatbot

Chattez avec Graph Search

Aggregating Spatial and Photometric Context for Photometric Stereo

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

Random matrix methods for high-dimensional machine learning models

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

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

Topics in statistical physics of high-dimensional machine learning

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

Aggregating Spatial and Photometric Context for Photometric Stereo

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

Random matrix methods for high-dimensional machine learning models

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

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

Topics in statistical physics of high-dimensional machine learning

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Deep Learning Theory Through the Lens of Diagonal Linear Networks

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

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