Speeding-up pruning for Artificial Neural Networks: Introducing Accelerated Iterative Magnitude Pruning. - Marco Zullich; Eric Medvet; Felice Andrea Pellegrino; Alessio Ansuini (ICPR, 2020)

On the Similarity between Hidden Layers of Pruned and Unpruned Convolutional Neural Networks. - Alessio Ansuini; Eric Medvet; Felice Andrea Pellegrino; Marco Zullich (ICPRAM, 2020)

Investigating Similarity Metrics for Convolutional Neural Networks in the Case of Unstructured Pruning. - Alessio Ansuini; Eric Medvet; Felice Andrea Pellegrino; Marco Zullich (ICPRAM (Revised Selected Papers), 2020)

On the effects of pruning on evolved neural controllers for soft robots. - Giorgia Nadizar; Eric Medvet; Felice Andrea Pellegrino; Marco Zullich; Stefano Nichele (GECCO Companion, 2021)

YOLO-Based Face Mask Detection on Low-End Devices Using Pruning and Quantization. - Benedetta Liberatori; Ciro Antonio Mami; Giovanni Santacatterina; Marco Zullich; Felice Andrea Pellegrino (MIPRO, 2022)

Merging pruning and neuroevolution: towards robust and efficient controllers for modular soft robots. - Giorgia Nadizar; Eric Medvet; Ola Huse Ramstad; Stefano Nichele; Felice Andrea Pellegrino; Marco Zullich (Knowl. Eng. Rev., 2022)

Merging pruning and neuroevolution: towards robust and efficient controllers for modular soft robots - Corrigendum. - Giorgia Nadizar; Eric Medvet; Ola Huse Ramstad; Stefano Nichele; Felice Andrea Pellegrino; Marco Zullich (Knowl. Eng. Rev., 2022)

Assessing Fairness in Open-Source Face Mask Detection Algorithms. - Marco Zullich; Giovanni Santacatterina (HHAI Workshops, 2023)

Explainable Automated Anomaly Recognition in Failure Analysis: is Deep Learning Doing it Correctly? - Leonardo Arrighi; Sylvio Barbon Junior; Felice Andrea Pellegrino; Michele Simonato; Marco Zullich (xAI (2), 2023)

An Artificial Intelligence System for Automatic Recognition of Punches in Fourteenth-Century Panel Painting. - Marco Zullich; Vanja Macovaz; Giovanni Pinna; Felice Andrea Pellegrino (IEEE Access, 2023)

Evaluating the Quality of Saliency Maps for Distilled Convolutional Neural Networks. - Jasper Wilfling; Matias Valdenegro-Toro; Marco Zullich (ESANN, 2024)

Unified Uncertainties: Combining Input, Data and Model Uncertainty into a Single Formulation. - Matias Valdenegro-Toro; Ivo Pascal de Jong; Marco Zullich (CoRR, 2024)

Large-Image Object Detection for Fine-Grained Recognition of Punches Patterns in Medieval Panel Painting. - Josh Bruegger; Diana Ioana Catana; Vanja Macovaz; Matias Valdenegro-Toro; Matthia Sabatelli; Marco Zullich (EvoMUSART, 2025)

Bridging Faithfulness of Explanations and Deep Reinforcement Learning: A Grad-CAM Analysis of Space Invaders. - Leendert Johannes Tanis; Rafael Fernandes Cunha; Marco Zullich (FDG, 2025)

Upside-Down Reinforcement Learning for More Interpretable Optimal Control. - Juan Cardenas-Cartagena; Massimiliano Falzari; Marco Zullich; Matthia Sabatelli (ICAART (1), 2025)

Uncertainty Estimation for Super-Resolution Using ESRGAN. - Maniraj Sai Adapa; Marco Zullich; Matias Valdenegro-Toro (VISIGRAPP (2): VISAPP, 2025)

Adaptive Prompt Tuning: Vision Guided Prompt Tuning with Cross-Attention for Fine-Grained Few-Shot Learning. - Eric Brouwer; Jan Erik van Woerden; Gertjan J. Burghouts; Matias Valdenegro-Toro; Marco Zullich (VISIGRAPP (2): VISAPP, 2025)

Can Bayesian Neural Networks Explicitly Model Input Uncertainty? - Matias Valdenegro-Toro; Marco Zullich (VISIGRAPP (3): VISAPP, 2025)

Sparsity-Driven Plasticity in Multi-Task Reinforcement Learning. - Aleksandar Todorov; Juan Cardenas-Cartagena; Rafael Fernandes Cunha; Marco Zullich; Matthia Sabatelli (Trans. Mach. Learn. Res., 2025)

Explainable Artificial Intelligence techniques for interpretation of food datasets: a review. - Leonardo Arrighi; Ingrid Alves de Moraes; Marco Zullich; Michele Simonato; Douglas Fernandes Barbin; Sylvio Barbon Junior (CoRR, 2025)