University of Cambridge > Talks.cam > Artificial Intelligence Research Group Talks (Computer Laboratory) > Rule extraction from deep neural nets

  Browse A-Z

Log in

Googledetails Microsoftdetails

🔐 Log In

Information on

Subscribing to talksdetails Finding a talkdetails Adding a talkdetails Disseminating talksdetails Help and Documentationdetails

ℹ️ Information

Rule extraction from deep neural nets

Download to your calendar using vCal

If you have a question about this talk, please contact Mateja Jamnik .

Deep neural nets are a black box approach to statistical learning. The classification from the model is hard to interpret. We present an approach to extracting rules from a deep learning model that gets cancer patients’ gene expression as input and classifies them as those likely or unlikely to relapse. In this way we get some level of explainability of the output from the deep learning model.

This talk is part of the Artificial Intelligence Research Group Talks (Computer Laboratory) series.

This talk is included in these lists:

Note that ex-directory lists are not shown.

Other lists

BAS Seminar Room 1; https://bas-ac-uk.zoom.us/j/94373277038 Whiston Society Science Talks http://map.cam.ac.uk/Office+of++Postdoctoral+Affairs?loc=2#52.176300,0.143277,18

Other talks

Science & the Public in Action: Can and should climate scientists be activists? Tea and Coffee Break Morning Break Talk TBC The Neurophenomenology of Surrender: Agency, Renewal, and Social Engagement in Speaking in Tongues Title TBC
 

© 2006-2025 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity