Publication

Geometric robustness of deep networks: analysis and improvement

Related publications (79)

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.

Geometric robustness of deep networks: analysis and improvement

Graph Chatbot

Chat with Graph Search

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

A geometry-inspired decision-based attack

Biologically plausible deep learning – but how far can we go with shallow networks?

An improved objective metric to predict image quality using deep neural networks

SparseFool: a few pixels make a big difference

Geometry of adversarial robustness of deep networks: methods and applications

Non-filamentary non-volatile memory elements as synapses in neuromorphic systems

Entropy and mutual information in models of deep neural networks

Jamming transition as a paradigm to understand the loss landscape of deep neural networks

Pretraining boosts out-of-domain robustness for pose estimation