Daniel L. Marino

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 33

Top Topics

Load Forecasting

Machine Learning

Top Venues

Publications

Walid Al Misba, Harindra S. Mavikumbure, Md Mahadi Rajib, Daniel L. Marino, Victor Cobilean, Milos Manic, Jayasimha Atulasimha
Spintronic Physical Reservoir for Autonomous Prediction and Long-Term Household Energy Load Forecasting. CoRR (2023)
Walid Al Misba, Harindra S. Mavikumbure, Md Mahadi Rajib, Daniel L. Marino, Victor Cobilean, Milos Manic, Jayasimha Atulasimha
Spintronic Physical Reservoir for Autonomous Prediction and Long-Term Household Energy Load Forecasting. IEEE Access 11 (2023)
Chathurika S. Wickramasinghe, Daniel L. Marino, Harindra S. Mavikumbure, Victor Cobilean, Timothy D. Pennington, Benny J. Varghese, Craig Rieger, Milos Manic
RX-ADS: Interpretable Anomaly Detection Using Adversarial ML for Electric Vehicle CAN Data. IEEE Trans. Intell. Transp. Syst. 24 (12) (2023)
Chathurika S. Wickramasinghe, Daniel L. Marino, Kasun Amarasinghe
Editorial: Explainable artificial intelligence. Frontiers Comput. Sci. 5 (2023)
Victor Cobilean, Harindra S. Mavikumbure, Chathurika S. Wickramasinghe, Daniel L. Marino, Milos Manic
Informed Deep Learning for Anomaly Detection in Cyber-Physical Systems. ICIT (2023)
Daniel L. Marino, Chathurika S. Wickramasinghe, Craig Rieger, Milos Manic
Self-Supervised and Interpretable Anomaly Detection using Network Transformers. CoRR (2022)
Harindra S. Mavikumbure, Chathurika S. Wickramasinghe, Daniel L. Marino, Victor Cobilean, Milos Manic
Anomaly Detection in Critical-Infrastructures using Autoencoders: A Survey. IECON (2022)
Sergio Vazquez, Daniel L. Marino, Eduardo Zafra, María Dolores Valdés Peña, Juan J. Rodríguez-Andina, Leopoldo García Franquelo, Milos Manic
An Artificial Intelligence Approach for Real-Time Tuning of Weighting Factors in FCS-MPC for Power Converters. IEEE Trans. Ind. Electron. 69 (12) (2022)
Chathurika S. Wickramasinghe, Daniel L. Marino, Harindra S. Mavikumbure, Victor Cobilean, Timothy D. Pennington, Benny J. Varghese, Craig Rieger, Milos Manic
RX-ADS: Interpretable Anomaly Detection using Adversarial ML for Electric Vehicle CAN data. CoRR (2022)
Daniel L. Marino, Chathurika S. Wickramasinghe, Billy Tsouvalas, Craig Rieger, Milos Manic
Data-Driven Correlation of Cyber and Physical Anomalies for Holistic System Health Monitoring. IEEE Access 9 (2021)
Chathurika S. Wickramasinghe, Daniel L. Marino, Milos Manic
ResNet Autoencoders for Unsupervised Feature Learning From High-Dimensional Data: Deep Models Resistant to Performance Degradation. IEEE Access 9 (2021)
Chathurika S. Wickramasinghe, Kasun Amarasinghe, Daniel L. Marino, Craig Rieger, Milos Manic
Explainable Unsupervised Machine Learning for Cyber-Physical Systems. IEEE Access 9 (2021)
Chathurika S. Wickramasinghe, Daniel L. Marino, Milos Manic
Deep Embedded Clustering with ResNets. HSI (2021)
Daniel L. Marino, Chathurika S. Wickramasinghe, Vivek Kumar Singh, Jake Gentle, Craig Rieger, Milos Manic
The Virtualized Cyber-Physical Testbed for Machine Learning Anomaly Detection: A Wind Powered Grid Case Study. IEEE Access 9 (2021)
Daniel L. Marino, Javier Grandio, Chathurika S. Wickramasinghe, Kyle Schroeder, Keith Bourne, Afroditi V. Filippas, Milos Manic
AI Augmentation for Trustworthy AI: Augmented Robot Teleoperation. HSI (2020)
Chathurika S. Wickramasinghe, Daniel L. Marino, Javier Grandio, Milos Manic
Trustworthy AI Development Guidelines for Human System Interaction. HSI (2020)
Daniel L. Marino, Milos Manic
Modeling and Planning Under Uncertainty Using Deep Neural Networks. IEEE Trans. Ind. Informatics 15 (8) (2019)
Daniel L. Marino, Milos Manic
Combining Physics-Based Domain Knowledge and Machine Learning using Variational Gaussian Processes with Explicit Linear Prior. CoRR (2019)
Morgan Stuart, Chathurika S. Wickramasinghe, Daniel L. Marino, Deepak Kumbhare, Kathryn Holloway, Milos Manic
Machine Learning for Deep Brain Stimulation Efficacy using Dense Array EEG. HSI (2019)
Daniel L. Marino, Chathurika S. Wickramasinghe, Craig Rieger, Milos Manic
Data-driven Stochastic Anomaly Detection on Smart-Grid communications using Mixture Poisson Distributions. IECON (2019)
Chathurika S. Wickramasinghe, Kasun Amarasinghe, Daniel L. Marino, Zachary A. Spielman, Ira E. Pray, David Gertman, Milos Manic
Intelligent Driver System for Improving Fuel Efficiency in Vehicle Fleets. HSI (2019)
Chathurika S. Wickramasinghe, Daniel L. Marino, Fatih Yucel, Eyuphan Bulut, Milos Manic
Data Driven Hourly Taxi Drop-offs Prediction using TLC Trip Record Data. HSI (2019)
Chathurika S. Wickramasinghe, Daniel L. Marino, Kasun Amarasinghe, Milos Manic
Generalization of Deep Learning for Cyber-Physical System Security: A Survey. IECON (2018)
Daniel L. Marino, Chathurika S. Wickramasinghe, Milos Manic
An Adversarial Approach for Explainable AI in Intrusion Detection Systems. IECON (2018)
Chathurika S. Wickramasinghe, Kasun Amarasinghe, Daniel L. Marino, Milos Manic
Deep Self-Organizing Maps for Visual Data Mining. HSI (2018)
Daniel L. Marino, Matthew Anderson, Kevin Kenney, Milos Manic
Interpretable Data-Driven Modeling in Biomass Preprocessing. HSI (2018)
Daniel L. Marino, Chathurika S. Wickramasinghe, Milos Manic
An Adversarial Approach for Explainable AI in Intrusion Detection Systems. CoRR (2018)
Kasun Amarasinghe, Daniel L. Marino, Milos Manic
Deep neural networks for energy load forecasting. ISIE (2017)
Daniel L. Marino, Kasun Amarasinghe, Milos Manic
Building Energy Load Forecasting using Deep Neural Networks. CoRR (2016)
Daniel L. Marino, Kasun Amarasinghe, Milos Manic
Simultaneous generation-classification using LSTM. SSCI (2016)
Daniel L. Marino, Milos Manic
Fast Trajectory Simplification Algorithm for Natural User Interfaces in Robot Programming by Demonstration. CoRR (2016)
Daniel L. Marino, Kasun Amarasinghe, Milos Manic
Building energy load forecasting using Deep Neural Networks. IECON (2016)
Daniel L. Marino, Milos Manic
Fast trajectory simplification algorithm for natural user interfaces in Robot programming by demonstration. ISIE (2016)