Enabling Container Cluster Interoperability using a TOSCA Orchestration Framework. - Domenico Calcaterra; Giuseppe Di Modica; Pietro Mazzaglia; Orazio Tomarchio (CLOSER, 2020)

Cluster-Agnostic Orchestration of Containerised Applications. - Domenico Calcaterra; Giuseppe Di Modica; Pietro Mazzaglia; Orazio Tomarchio (CLOSER (Selected Papers), 2020)

Contrastive Active Inference. - Pietro Mazzaglia; Tim Verbelen; Bart Dhoedt (NeurIPS, 2021)

Self-Supervised Exploration via Latent Bayesian Surprise. - Pietro Mazzaglia; Ozan Çatal; Tim Verbelen; Bart Dhoedt (CoRR, 2021)

A learning gap between neuroscience and reinforcement learning. - Samuel T. Wauthier; Pietro Mazzaglia; Ozan Çatal; Cedric De Boom; Tim Verbelen; Bart Dhoedt (CoRR, 2021)

TORCH: a TOSCA-Based Orchestrator of Multi-Cloud Containerised Applications. - Orazio Tomarchio; Domenico Calcaterra; Giuseppe Di Modica; Pietro Mazzaglia (J. Grid Comput., 2021)

Curiosity-Driven Exploration via Latent Bayesian Surprise. - Pietro Mazzaglia; Ozan Çatal; Tim Verbelen; Bart Dhoedt (AAAI, 2022)

Disentangling Shape and Pose for Object-Centric Deep Active Inference Models. - Stefano Ferraro; Toon Van de Maele; Pietro Mazzaglia; Tim Verbelen; Bart Dhoedt (IWAI, 2022)

Home Run: Finding Your Way Home by Imagining Trajectories. - Daria de Tinguy; Pietro Mazzaglia; Tim Verbelen; Bart Dhoedt (IWAI, 2022)

Unsupervised Model-based Pre-training for Data-efficient Control from Pixels. - Sai Rajeswar; Pietro Mazzaglia; Tim Verbelen; Alexandre Piché; Bart Dhoedt; Aaron C. Courville; Alexandre Lacoste (CoRR, 2022)

The Free Energy Principle for Perception and Action: A Deep Learning Perspective. - Pietro Mazzaglia; Tim Verbelen; Ozan Çatal; Bart Dhoedt (Entropy, 2022)

Computational Optimization of Image-Based Reinforcement Learning for Robotics. - Stefano Ferraro; Toon Van de Maele; Pietro Mazzaglia; Tim Verbelen; Bart Dhoedt (Sensors, 2022)

Choreographer: Learning and Adapting Skills in Imagination. - Pietro Mazzaglia; Tim Verbelen; Bart Dhoedt; Alexandre Lacoste; Sai Rajeswar (ICLR, 2023)

Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels. - Sai Rajeswar; Pietro Mazzaglia; Tim Verbelen; Alexandre Piché; Bart Dhoedt; Aaron C. Courville; Alexandre Lacoste (ICML, 2023)

FOCUS: Object-Centric World Models for Robotics Manipulation. - Stefano Ferraro; Pietro Mazzaglia; Tim Verbelen; Bart Dhoedt (CoRR, 2023)

Uncertainty-driven Affordance Discovery for Efficient Robotics Manipulation. - Pietro Mazzaglia; Taco Cohen; Daniel Dijkman (CoRR, 2023)

Learning to Navigate from Scratch using World Models and Curiosity: the Good, the Bad, and the Ugly. - Daria de Tinguy; Sven Remmery; Pietro Mazzaglia; Tim Verbelen; Bart Dhoedt (CoRR, 2023)

Information-driven Affordance Discovery for Efficient Robotic Manipulation. - Pietro Mazzaglia; Taco Cohen; Daniel Dijkman (ICRA, 2024)

GenRL: Multimodal-foundation world models for generalization in embodied agents. - Pietro Mazzaglia; Tim Verbelen; Bart Dhoedt; Aaron C. Courville; Sai Rajeswar Mudumba (NeurIPS, 2024)

Multimodal foundation world models for generalist embodied agents. - Pietro Mazzaglia; Tim Verbelen; Bart Dhoedt; Aaron C. Courville; Sai Rajeswar (CoRR, 2024)

Representing Positional Information in Generative World Models for Object Manipulation. - Stefano Ferraro; Pietro Mazzaglia; Tim Verbelen; Bart Dhoedt; Sai Rajeswar (CoRR, 2024)

Object-Centric Scene Representations Using Active Inference. - Toon Van de Maele; Tim Verbelen; Pietro Mazzaglia; Stefano Ferraro; Bart Dhoedt (Neural Comput., 2024)

Redundancy-Aware Action Spaces for Robot Learning. - Pietro Mazzaglia; Nicholas Backshall; Xiao Ma 006; Stephen James (IEEE Robotics Autom. Lett., 2024)

FOCUS: object-centric world models for robotic manipulation. - Stefano Ferraro; Pietro Mazzaglia; Tim Verbelen; Bart Dhoedt (Frontiers Neurorobotics, 2025)

Maximum causal entropy inverse constrained reinforcement learning. - Mattijs Baert; Pietro Mazzaglia; Sam Leroux; Pieter Simoens (Mach. Learn., 2025)