Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Interpretability of deep learning models: a survey of results

Chakraborty, Supriyo, Tomsett, Richard, Raghavendra, Ramya, Harborne, Daniel, Alzantot, Moustafa, Cerutti, Federico, Srivastava, Mani, Preece, Alun David, Julier, Simon, Rao, Raghuveer M., Kelley, Troy D., Braines, David, Sensoy, Murat, Willis, Christopher J. and Gurram, Prudhvi 2017. Interpretability of deep learning models: a survey of results. Presented at: IEEE Smart World Congress 2017 Workshop: DAIS 2017 - Workshop on Distributed Analytics InfraStructure and Algorithms for Multi-Organization Federations, San Francisco, CA, USA, 7-8 August 2017.

[thumbnail of Interpretability of Deep Learning Models - A Survey of Results.pdf]
PDF - Accepted Post-Print Version
Download (105kB) | Preview
Item Type: Conference or Workshop Item (Paper)
Date Type: Completion
Status: Unpublished
Schools: Computer Science & Informatics
Crime and Security Research Institute (CSURI)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Related URLs:
Date of First Compliant Deposit: 16 June 2017
Last Modified: 22 May 2022 07:26

Actions (repository staff only)

Edit Item Edit Item


Downloads per month over past year

View more statistics