Publication

Sound and Complete Verification of Polynomial Networks

Related publications (50)

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.

Sound and Complete Verification of Polynomial Networks

Graph Chatbot

Chat with Graph Search

Regularization of polynomial networks for image recognition

Regularization of polynomial networks for image recognition

Deep Learning Generalization with Limited and Noisy Labels

An exact mapping from ReLU networks to spiking neural networks

Improving the Training of Compact Neural Networks for Visual Recognition

The spectral bias of polynomial neural networks

An anomaly detection approach for backdoored neural networks: face recognition as a case study

An anomaly detection approach for backdoored neural networks: face recognition as a case study

Adjustable deterministic pseudonymization of speech

Perceiving Humans: from Monocular 3D Localization to Social Distancing

Deep Learning Generalization with Limited and Noisy Labels

An exact mapping from ReLU networks to spiking neural networks

The spectral bias of polynomial neural networks

Improving the Training of Compact Neural Networks for Visual Recognition

Perceiving Humans: from Monocular 3D Localization to Social Distancing

Adjustable deterministic pseudonymization of speech

Regularization of polynomial networks for image recognition

Regularization of polynomial networks for image recognition

An anomaly detection approach for backdoored neural networks: face recognition as a case study

An anomaly detection approach for backdoored neural networks: face recognition as a case study