Pietro Mazzaglia

Orcid: 0000-0003-3319-5986

According to our database¹, Pietro Mazzaglia authored at least 23 papers between 2020 and 2024.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

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In proceedings

Article

PhD thesis

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Bibliography

2024

Redundancy-Aware Action Spaces for Robot Learning.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., August, 2024

Object-Centric Scene Representations Using Active Inference.

[BibT_eX]

[DOI]

Neural Comput., April, 2024

Representing Positional Information in Generative World Models for Object Manipulation.

[BibT_eX]

[DOI]

CoRR, 2024

Multimodal foundation world models for generalist embodied agents.

[BibT_eX]

[DOI]

CoRR, 2024

Information-driven Affordance Discovery for Efficient Robotic Manipulation.

[BibT_eX]

[DOI]

Pietro Mazzaglia

Taco Cohen

Daniel Dijkman

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

2023

Learning to Navigate from Scratch using World Models and Curiosity: the Good, the Bad, and the Ugly.

[BibT_eX]

[DOI]

CoRR, 2023

Uncertainty-driven Affordance Discovery for Efficient Robotics Manipulation.

[BibT_eX]

[DOI]

Pietro Mazzaglia

Taco Cohen

Daniel Dijkman

CoRR, 2023

FOCUS: Object-Centric World Models for Robotics Manipulation.

[BibT_eX]

[DOI]

CoRR, 2023

Maximum Causal Entropy Inverse Constrained Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Choreographer: Learning and Adapting Skills in Imagination.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Computational Optimization of Image-Based Reinforcement Learning for Robotics.

[BibT_eX]

[DOI]

Sensors, 2022

The Free Energy Principle for Perception and Action: A Deep Learning Perspective.

[BibT_eX]

[DOI]

Entropy, 2022

Unsupervised Model-based Pre-training for Data-efficient Control from Pixels.

[BibT_eX]

[DOI]

CoRR, 2022

Home Run: Finding Your Way Home by Imagining Trajectories.

[BibT_eX]

[DOI]

Proceedings of the Active Inference - Third International Workshop, 2022

Disentangling Shape and Pose for Object-Centric Deep Active Inference Models.

[BibT_eX]

[DOI]

Proceedings of the Active Inference - Third International Workshop, 2022

Curiosity-Driven Exploration via Latent Bayesian Surprise.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

TORCH: a TOSCA-Based Orchestrator of Multi-Cloud Containerised Applications.

[BibT_eX]

[DOI]

J. Grid Comput., 2021

A learning gap between neuroscience and reinforcement learning.

[BibT_eX]

[DOI]

CoRR, 2021

Self-Supervised Exploration via Latent Bayesian Surprise.

[BibT_eX]

[DOI]

CoRR, 2021

Contrastive Active Inference.

[BibT_eX]

[DOI]

Pietro Mazzaglia

Tim Verbelen

Bart Dhoedt

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Cluster-Agnostic Orchestration of Containerised Applications.

[BibT_eX]

[DOI]

Proceedings of the Cloud Computing and Services Science - 10th International Conference, 2020

Enabling Container Cluster Interoperability using a TOSCA Orchestration Framework.

[BibT_eX]

[DOI]

Proceedings of the 10th International Conference on Cloud Computing and Services Science, 2020

Pietro Mazzaglia

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