Publication

From Kernel Methods to Neural Networks: A Unifying Variational Formulation

Related publications (293)

About
Privacy
Disclaimer

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

From Kernel Methods to Neural Networks: A Unifying Variational Formulation

Graph Chatbot

Chat with Graph Search

Efficient local linearity regularization to overcome catastrophic overfitting

Digital Twins of Stone Masonry Buildings for Damage Assessment

ProGAP: Progressive Graph Neural Networks with Differential Privacy Guarantees

Deep Learning Generalization with Limited and Noisy Labels

Benign Overfitting in Deep Neural Networks under Lazy Training

Supervised learning and inference of spiking neural networks with temporal coding

Robust Training and Verification of Deep Neural Networks

Breaking the Curse of Dimensionality in Deep Neural Networks by Learning Invariant Representations

An exact mapping from ReLU networks to spiking neural networks

Bayes-optimal Learning of Deep Random Networks of Extensive-width