no code implementations • 12 Apr 2024 • Alexander Sommers, Somayeh Bakhtiari Ramezani, Logan Cummins, Sudip Mittal, Shahram Rahimi, Maria Seale, Joseph Jaboure
Data augmentation is an important facilitator of deep learning applications in the time series domain.
no code implementations • 18 Jan 2024 • Jesse Ables, Nathaniel Childers, William Anderson, Sudip Mittal, Shahram Rahimi, Ioana Banicescu, Maria Seale
The contributions of this work include the hybrid X-IDS architecture, the eclectic rule extraction algorithm applicable to intrusion detection datasets, and a thorough analysis of performance and explainability, demonstrating the trade-offs involved in rule extraction speed and accuracy.
Explainable artificial intelligence Explainable Artificial Intelligence (XAI) +2
no code implementations • 15 Jan 2024 • Logan Cummins, Alex Sommers, Somayeh Bakhtiari Ramezani, Sudip Mittal, Joseph Jabour, Maria Seale, Shahram Rahimi
This survey on explainable predictive maintenance (XPM) discusses and presents the current methods of XAI as applied to predictive maintenance while following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines.
no code implementations • 30 Mar 2023 • Jesse Ables, Thomas Kirby, Sudip Mittal, Ioana Banicescu, Shahram Rahimi, William Anderson, Maria Seale
Lastly, we analyze the statistical and visual explanations generated by our architecture, and we give a strategy that users could use to help navigate the set of explanations.
no code implementations • 16 Aug 2022 • William Anderson, Kaneesha Moore, Jesse Ables, Sudip Mittal, Shahram Rahimi, Ioana Banicescu, Maria Seale
The Human Immune System (HIS) works to protect a body from infection, illness, and disease.
no code implementations • 15 Jul 2022 • Jesse Ables, Thomas Kirby, William Anderson, Sudip Mittal, Shahram Rahimi, Ioana Banicescu, Maria Seale
We leverage SOM's explainability to create both global and local explanations.
Explainable artificial intelligence Explainable Artificial Intelligence (XAI) +2
no code implementations • 13 Jul 2022 • Subash Neupane, Jesse Ables, William Anderson, Sudip Mittal, Shahram Rahimi, Ioana Banicescu, Maria Seale
The application of Artificial Intelligence (AI) and Machine Learning (ML) to cybersecurity challenges has gained traction in industry and academia, partially as a result of widespread malware attacks on critical systems such as cloud infrastructures and government institutions.
Explainable Artificial Intelligence (XAI) Intrusion Detection