Publication

A deep learning framework for matching of SAR and optical imagery

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 A deep learning framework for matching of SAR and optical imagery | 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

A deep learning framework for matching of SAR and optical imagery

Graph Chatbot

Chattez avec Graph Search

Aggregating Spatial and Photometric Context for Photometric Stereo

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

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

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

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Robust machine learning for neuroscientific inference

Generalization of Scaled Deep ResNets in the Mean-Field Regime

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

Aggregating Spatial and Photometric Context for Photometric Stereo

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

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

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

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

Robust machine learning for neuroscientific inference

Generalization of Scaled Deep ResNets in the Mean-Field Regime

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

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning