Autonomous agent based on reinforcement learning and adaptive shadowed network. - Bojan Jerbic; Katarina Grolinger; Bozo Vranjs (Artif. Intell. Eng., 1999)

Data Providing Web Service-based integration framework for use in a health care context. - Kevin P. Brown; Katarina Grolinger; Miriam A. M. Capretz (CCECE, 2011)

Federated critical infrastructure simulators: Towards ontologies for support of collaboration. - Katarina Grolinger; Miriam A. M. Capretz; Adam Shypanski; Gagandeep S. Gill (CCECE, 2011)

From Glossaries to Ontologies: Disaster Management Domain(S). - Katarina Grolinger; Kevin P. Brown; Miriam A. M. Capretz (SEKE, 2011)

A unit test approach for database schema evolution. - Katarina Grolinger; Miriam A. M. Capretz (Inf. Softw. Technol., 2011)

Ontology-based Representation of Simulation Models. - Katarina Grolinger; Miriam A. M. Capretz; José R. Martí; Krishan D. Srivastava (SEKE, 2012)

Knowledge as a Service Framework for Disaster Data Management. - Katarina Grolinger; Miriam A. M. Capretz; Emna Mezghani; Ernesto Exposito (WETICE, 2013)

Data management in cloud environments: NoSQL and NewSQL data stores. - Katarina Grolinger; Wilson A. Higashino; Abhinav Tiwari; Miriam A. M. Capretz (J. Cloud Comput., 2013)

Challenges for MapReduce in Big Data. - Katarina Grolinger; Michael A. Hayes; Wilson A. Higashino; Alexandra L'Heureux; David S. Allison; Miriam A. M. Capretz (SERVICES, 2014)

Integration of business process modeling and Web services: a survey. - Katarina Grolinger; Miriam A. M. Capretz; Americo Cunha; Saïd Tazi 001 (Serv. Oriented Comput. Appl., 2014)

A Generalized Service Replication Process in Distributed Environments. - Hany F. El Yamany; Marwa F. Mohamed; Katarina Grolinger; Miriam A. M. Capretz (CLOSER, 2015)

Predicting Energy Demand Peak Using M5 Model Trees. - Sara S. Abdelkader; Katarina Grolinger; Miriam A. M. Capretz (ICMLA, 2015)

MLaaS: Machine Learning as a Service. - Mauro Ribeiro; Katarina Grolinger; Miriam A. M. Capretz (ICMLA, 2015)

Collaborative knowledge as a service applied to the disaster management domain. - Katarina Grolinger; Emna Mezghani; Miriam A. M. Capretz; Ernesto Exposito (Int. J. Cloud Comput., 2015)

Energy Consumption Prediction with Big Data: Balancing Prediction Accuracy and Computational Resources. - Katarina Grolinger; Miriam A. M. Capretz; Luke Seewald (BigData Congress, 2016)

Collective contextual anomaly detection framework for smart buildings. - Daniel B. Araya; Katarina Grolinger; Hany F. ElYamany; Miriam A. M. Capretz; Girma T. Bitsuamlak (IJCNN, 2016)

A Gamification Framework for Sensor Data Analytics. - Alexandra L'Heureux; Katarina Grolinger; Wilson A. Higashino; Miriam A. M. Capretz (ICIOT, 2017)

Deep Neural Networks with Confidence Sampling for Electrical Anomaly Detection. - Norman L. Tasfi; Wilson A. Higashino; Katarina Grolinger; Miriam A. M. Capretz (iThings/GreenCom/CPSCom/SmartData, 2017)

Machine Learning With Big Data: Challenges and Approaches. - Alexandra L'Heureux; Katarina Grolinger; Hany F. ElYamany; Miriam A. M. Capretz (IEEE Access, 2017)

Forecasting Residential Energy Consumption: Single Household Perspective. - Xiaoou Monica Zhang; Katarina Grolinger; Miriam A. M. Capretz; Luke Seewald (ICMLA, 2018)

(CF)2 architecture: contextual collaborative filtering. - Dennis Bachmann; Katarina Grolinger; Hany F. ElYamany; Wilson A. Higashino; Miriam A. M. Capretz; Majid Fekri; Bala Gopalakrishnan (Inf. Retr. J., 2018)

Deep Learning: Edge-Cloud Data Analytics for IoT. - Ananda Mohon Ghosh; Katarina Grolinger (CCECE, 2019)

Forecasting Building Energy Consumption with Deep Learning: A Sequence to Sequence Approach. - Ljubisa Sehovac; Cornelius Nesen; Katarina Grolinger (ICIOT, 2019)

Similarity-Based Chained Transfer Learning for Energy Forecasting With Big Data. - Yifang Tian; Ljubisa Sehovac; Katarina Grolinger (IEEE Access, 2019)

ServeNet: A Deep Neural Network for Web Services Classification. - Yilong Yang 001; Nafees Qamar; Peng Liu 070; Katarina Grolinger; Weiru Wang 001; Zhi Li 017; Zhifang Liao (ICWS, 2020)

Deep Neural Networks for Human Activity Recognition With Wearable Sensors: Leave-One-Subject-Out Cross-Validation for Model Selection. - Davoud Gholamiangonabadi; Nikita Kiselov; Katarina Grolinger (IEEE Access, 2020)

Deep Learning for Load Forecasting: Sequence to Sequence Recurrent Neural Networks With Attention. - Ljubisa Sehovac; Katarina Grolinger (IEEE Access, 2020)

Reinforcement Learning Algorithms: An Overview and Classification. - Fadi AlMahamid; Katarina Grolinger (CCECE, 2021)

Load Forecasting Under Concept Drift: Online Ensemble Learning With Recurrent Neural Network and ARIMA. - Rashpinder Kaur Jagait; Mohammad Navid Fekri; Katarina Grolinger; Syed Mir (IEEE Access, 2021)

Deep Learning for High-Impedance Fault Detection: Convolutional Autoencoders. - Khushwant Rai; Farnam Hojatpanah; Firouz Badrkhani Ajaei; Katarina Grolinger (CoRR, 2021)

Edge-Cloud Computing for Internet of Things Data Analytics: Embedding Intelligence in the Edge With Deep Learning. - Ananda Mohon Ghosh; Katarina Grolinger (IEEE Trans. Ind. Informatics, 2021)

Agglomerative Hierarchical Clustering with Dynamic Time Warping for Household Load Curve Clustering. - Fadi AlMahamid; Katarina Grolinger (CCECE, 2022)

Virtual Sensor Middleware: Managing IoT Data for the Fog-Cloud Platform. - Fadi AlMahamid; Hanan Lutfiyya; Katarina Grolinger (CCECE, 2022)

Malicious and Benign URL Dataset Generation Using Character-Level LSTM Models. - Spencer Vecile; Kyle Lacroix; Katarina Grolinger; Jagath Samarabandu (DSC, 2022)

Comparison of Machine Learning Techniques for Activities of Daily Living Classification with Electromyographic Data. - Sergio A. Salinas; Mohamed Ahmed T. A. Elgalhud; Luke Tambakis; Sanket Vilas Salunke; Kshitija Patel; Hamada H. Ghenniwa; Abdelkader Ouda; Kenneth A. McIsaac; Katarina Grolinger; Ana Luisa Trejos (ICORR, 2022)

Autonomous Unmanned Aerial Vehicle navigation using Reinforcement Learning: A systematic review. - Fadi AlMahamid; Katarina Grolinger (Eng. Appl. Artif. Intell., 2022)

Deep learning for high-impedance fault detection and classification: transformer-CNN. - Khushwant Rai; Farnam Hojatpanah; Firouz Badrkhani Ajaei; Josep M. Guerrero; Katarina Grolinger (Neural Comput. Appl., 2022)

Data Augmentation for Deep-Learning-Based Multiclass Structural Damage Detection Using Limited Information. - Kyle Dunphy; Mohammad Navid Fekri; Katarina Grolinger; Ayan Sadhu (Sensors, 2022)

Improving Adversarial Robustness of Few-Shot Learning with Contrastive Learning and Hypersphere Embedding. - Madhushan Buwaneswaran; Tehara Fonseka; Apurva Narayan; Katarina Grolinger (ICMLA, 2023)

Scheduling Electric Vehicle Charging for Grid Load Balancing. - Zhixin Han; Katarina Grolinger; Miriam A. M. Capretz; Syed Mir (IECON, 2023)

Interval Load Forecasting for Individual Households in the Presence of Electric Vehicle Charging. - Raiden Skala; Mohamed Ahmed T. A. Elgalhud; Katarina Grolinger; Syed Mir (CoRR, 2023)

Personalized models for human activity recognition with wearable sensors: deep neural networks and signal processing. - Davoud Gholamiangonabadi; Katarina Grolinger (Appl. Intell., 2023)

Evaluating Mixed Reality Technology for Tracking Hand Motion for Shoulder Rehabilitation Assessment. - Sergio A. Salinas; Katarina Grolinger; Marie-Eve LeBel; Ana Luisa Trejos (BioRob, 2024)

Clustered Federated Learning with Non-IID Data: Mitigating Accuracy Overestimates Through Hold-Out Model Selection and Evaluation. - Davoud Gholamiangonabadi; Katarina Grolinger (ICMLA, 2024)

Temporally Chained Equations: An Interpretable Missing Data Imputation Approach for Smart Meters with Low Data Requirements. - Madhushan Buwaneswaran; Katarina Grolinger (IECON, 2024)

Graph Attention Convolutional U-NET: A Semantic Segmentation Model for Identifying Flooded Areas. - Muhammad Umair Danish; Madhushan Buwaneswaran; Tehara Fonseka; Katarina Grolinger (IECON, 2024)

ChebyRegNet: An Unsupervised Deep Learning Technique for Deformable Medical Image Registration. - Muhammad Umair Danish; Mohammad Noorchenarboo; Apurva Narayan; Katarina Grolinger (IECON, 2024)

Performance Analysis of Dilated One-to-Many U-Net Model for Medical Image Segmentation. - Vahid Ashkani Chenarlogh; Arman Hassanpour; Katarina Grolinger; Vijay Parsa (IEEE Access, 2024)

Federated Learning for Sentiment Analysis in Presence of Non-IID Data: Sensitivity of Deep Learning Models. - Davoud Gholamiangonabadi; Katarina Grolinger (IEEE Access, 2024)

Remote collaborative framework for real-time structural condition assessment using Augmented Reality. - Omar Awadallah; Katarina Grolinger; Ayan Sadhu (Adv. Eng. Informatics, 2024)

Estimating Thorax and Shoulder Motion Using Magnetic-Free Quaternion-Based Functional Sensor-To-Segment Calibration. - Sergio A. Salinas; Mahshad Berjis; Katarina Grolinger; Ana Luisa Trejos (ICORR, 2025)

Few-Shot Learning Augmented with Image Transformation for Multiclass Structural Damage Classification. - Kyle Dunphy; Madhushan Buwaneswaran; Katarina Grolinger; Ayan Sadhu (J. Comput. Civ. Eng., 2025)

Explaining Deep Learning-based Anomaly Detection in Energy Consumption Data by Focusing on Contextually Relevant Data. - Mohammad Noorchenarboo; Katarina Grolinger (CoRR, 2025)

Kolmogorov-Arnold Recurrent Network for Short Term Load Forecasting Across Diverse Consumers. - Muhammad Umair Danish; Katarina Grolinger (CoRR, 2025)

Federated Learning for Anomaly Detection in Energy Consumption Data: Assessing the Vulnerability to Adversarial Attacks. - Yohannis Kifle Telila; Damitha Senevirathne; Dumindu Tissera; Apurva Narayan; Miriam A. M. Capretz; Katarina Grolinger (CoRR, 2025)

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types. - Muhammad Umair Danish; Katarina Grolinger (CoRR, 2025)

Global-Local Image Perceptual Score (GLIPS): Evaluating Photorealistic Quality of AI-Generated Images. - Memoona Aziz; Umair Rehman; Muhammad Umair Danish; Katarina Grolinger (IEEE Trans. Hum. Mach. Syst., 2025)

Any-Class Presence Likelihood for Robust Multi-Label Classification with Abundant Negative Data. - Dumindu Tissera; Omar Awadallah; Muhammad Umair Danish; Ayan Sadhu; Katarina Grolinger (CoRR, 2025)

Improving retail sales through unsupervised collective-contextual anomaly detection: a deep reconstruction autoencoder for network-wide sales analysis. - Tehara Fonseka; Anton Tulenkov; Katarina Grolinger (Appl. Intell., 2025)

Physics-Guided Memory Network for Building Energy Modeling. - Muhammad Umair Danish; Kashif Ali; Kamran Siddiqui; Katarina Grolinger (CoRR, 2025)