Publication

A new variable shape parameter strategy for RBF approximation using neural networks

Related publications (45)

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.

A new variable shape parameter strategy for RBF approximation using neural networks

Graph Chatbot

Chat with Graph Search

Privacy-preserving federated neural network training and inference

Leveraging Unlabeled Data to Track Memorization

Benign Overfitting in Deep Neural Networks under Lazy Training

A Neural-Network-Based Convex Regularizer for Inverse Problems

Theory of Deep Learning: Neural Tangent Kernel and Beyond

Deep Learning Detection of GPS Spoofing

Biologically plausible unsupervised learning in shallow and deep neural networks

What can linearized neural networks actually say about generalization?

Neural Tangent Kernel: Convergence and Generalization in Neural Networks (Invited Paper)

Multiscale Representation Learning of Graph Data With Node Affinity