View Proposal

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Proposer

Ekaterina Komendantskaya

Title

Verification of Neural Networks

Goal

Description

As machine learning algorithms find their ways in safety-critical systems, such as autonomous cars, robot nurses, conversational agents, the question of ensuring their safety and security becomes important. At the same time, neural networks are known to be vulnerable to adversarial attacks --- a special kind of crafted inputs that cause unintended behaviour in trained neural networks. Due to these two factors, neural network verification has become a hot topic in both machine learning and verification communities. It is often described as one of the main challenges faced by computer science and engineering these days. In this project, you will study the existing methods of neural network verification, and will implement your own toy application/algorithm. You will have a chance to collaborate with researchers in the lab for AI and Verification: LAIV.uk.

Resources

Background

Url

Difficulty Level

Variable

Ethical Approval

None

Number Of Students

4

Supervisor

Ekaterina Komendantskaya

Keywords

Degrees