Explaining probabilistic Artificial Intelligence (AI) models by discretizing Deep Neural Networks
Conference item
Saleem, Rabia, Yuan, Bo, Kurugollu, Fatih and Anjum, Ashiq 2020. Explaining probabilistic Artificial Intelligence (AI) models by discretizing Deep Neural Networks. IEEE. https://doi.org/10.1109/ucc48980.2020.00070
| Authors | Saleem, Rabia, Yuan, Bo, Kurugollu, Fatih and Anjum, Ashiq |
|---|---|
| Abstract | Artificial Intelligence (AI) models can learn from data and make decisions without any human intervention. However, the deployment of such models is challenging and risky because we do not know how the internal decisionmaking is happening in these models. Especially, the high-risk decisions such as medical diagnosis or automated navigation demand explainability and verification of the decision making process in AI algorithms. This research paper aims to explain Artificial Intelligence (AI) models by discretizing the black-box process model of deep neural networks using partial differential equations. The PDEs based deterministic models would minimize the time and computational cost of the decision-making process and reduce the chances of uncertainty that make the prediction more trustworthy. |
| Keywords | Artificial Intelligence; Deep Neural Networks; Partial differential equations; Discretization |
| Year | 2020 |
| Journal | 2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC) |
| 2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC) | |
| Publisher | IEEE |
| Digital Object Identifier (DOI) | https://doi.org/10.1109/ucc48980.2020.00070 |
| Web address (URL) | http://hdl.handle.net/10545/625606 |
| http://creativecommons.org/licenses/by-nc-sa/4.0/ | |
| hdl:10545/625606 | |
| ISBN | 9780738123943 |
| File | File Access Level Open |
| File | File Access Level Open |
| Publication dates | 30 Dec 2020 |
| Publication process dates | |
| Deposited | 08 Feb 2021, 15:50 |
| Accepted | 30 Oct 2020 |
| Rights | Attribution-NonCommercial-ShareAlike 4.0 International |
| Contributors | University of Derby and University of Leicester |
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Anjum, Ashiq, Hill, Richard, McClatchey, Richard, Bessis, Nik and Branson, Andrew 2012. Glueing grids and clouds together: a service-oriented approach. International Journal of Web and Grid Services. https://doi.org/10.1504/IJWGS.2012.049169Energy conservation in mobile devices and applications: a case for context parsing, processing and distribution in clouds
Kiani, Saad Liaquat, Anjum, Ashiq, Bessis, Nik, Hill, Richard and Knappmeyer, Michael 2013. Energy conservation in mobile devices and applications: a case for context parsing, processing and distribution in clouds. Mobile Information Systems.Approaching the Internet of things (IoT): a modelling, analysis and abstraction framework
Ikram, Ahsan, Anjum, Ashiq, Hill, Richard, Antonopoulos, Nikolaos, Liu, Lu and Sotiriadis, Stelios 2013. Approaching the Internet of things (IoT): a modelling, analysis and abstraction framework. Concurrency and Computation: Practice and Experience. https://doi.org/10.1002/cpe.3131Performance simulation of a context provisioning middleware based on empirical measurements
Reetz, Eike Steffen, Knappmeyer, Michael, Kiani, Saad Liaquat, Anjum, Ashiq, Bessis, Nik and Tönjes, Ralf 2012. Performance simulation of a context provisioning middleware based on empirical measurements. https://doi.org/10.1016/j.simpat.2012.03.002