Swarm Intelligence Approaches for Parameter Setting of Deep Learning Neural Network: Case Study on Phishing Websites Classification. - Grega Vrbancic; Iztok Fister Jr.; Vili Podgorelec (WIMS, 2018)

NiaPy: Python microframework for building nature-inspired algorithms. - Grega Vrbancic; Lucija Brezocnik; Uros Mlakar; Dusan Fister; Iztok Fister Jr. (J. Open Source Softw., 2018)

Applying Differential Evolution with Threshold Mechanism for Feature Selection on a Phishing Websites Classification. - Lucija Brezocnik; Iztok Fister Jr.; Grega Vrbancic (ADBIS (Short Papers and Workshops), 2019)

Parameter Setting for Deep Neural Networks Using Swarm Intelligence on Phishing Websites Classification. - Grega Vrbancic; Iztok Fister Jr.; Vili Podgorelec (Int. J. Artif. Intell. Tools, 2019)

On the Potential of the Nature-Inspired Algorithms for Pure Binary Classification. - Iztok Fister Jr.; Iztok Fister 001; Dusan Fister; Grega Vrbancic; Vili Podgorelec (ICCS (5), 2020)

Identification of COVID-19 X-ray Images using CNN with Optimized Tuning of Transfer Learning. - Grega Vrbancic; Spela Pecnik; Vili Podgorelec (INISTA, 2020)

Transfer Learning With Adaptive Fine-Tuning. - Grega Vrbancic; Vili Podgorelec (IEEE Access, 2020)

Synthetic Data Augmentation of Cycling Sport Training Datasets. - Iztok Fister 001; Grega Vrbancic; Vili Podgorelec; Iztok Fister Jr. (ICO, 2021)

Efficient ensemble for image-based identification of Pneumonia utilizing deep CNN and SGD with warm restarts. - Grega Vrbancic; Vili Podgorelec (Expert Syst. Appl., 2022)

Towards Green AI by Reducing Training Effort of Recurrent Neural Networks Using Hyper-Parameter Optimization with Dynamic Stopping Criteria. - Vili Podgorelec; Iztok Fister 001; Grega Vrbancic (SISY, 2024)

Employing Feature Engineering for River Stage Forecasting to Improve Hybrid Model Performance. - Anna Maria Mihel; Spela Pecnik; Grega Vrbancic; Jonatan Lerga; Nino Krvavica (SoftCOM, 2024)