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.

Preview

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Status:	Unpublished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:	Organisation
Last Modified:	29 Jul 2018 21:10
URI:	http://orca.cf.ac.uk/id/eprint/101500

Actions (repository staff only)

Edit Item