Pietro Mazzaglia | DeepAI

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∙ 08/30/2023

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

Learning to navigate unknown environments from scratch is a challenging ...

0 Daria de Tinguy, et al. ∙

∙ 08/28/2023

Uncertainty-driven Affordance Discovery for Efficient Robotics Manipulation

Robotics affordances, providing information about what actions can be ta...

0 Pietro Mazzaglia, et al. ∙

∙ 07/05/2023

FOCUS: Object-Centric World Models for Robotics Manipulation

Understanding the world in terms of objects and the possible interplays ...

0 Stefano Ferraro, et al. ∙

∙ 05/04/2023

Maximum Causal Entropy Inverse Constrained Reinforcement Learning

When deploying artificial agents in real-world environments where they i...

0 Mattijs Baert, et al. ∙

∙ 02/07/2023

Object-Centric Scene Representations using Active Inference

Representing a scene and its constituent objects from raw sensory data i...

0 Toon Van de Maele, et al. ∙

∙ 11/23/2022

Choreographer: Learning and Adapting Skills in Imagination

Unsupervised skill learning aims to learn a rich repertoire of behaviors...

0 Pietro Mazzaglia, et al. ∙

∙ 09/24/2022

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

Controlling artificial agents from visual sensory data is an arduous tas...

0 Sai Rajeswar, et al. ∙

∙ 09/16/2022

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

Active inference is a first principles approach for understanding the br...

3 Stefano Ferraro, et al. ∙

∙ 08/19/2022

Home Run: Finding Your Way Home by Imagining Trajectories

When studying unconstrained behaviour and allowing mice to leave their c...

0 Daria de Tinguy, et al. ∙

∙ 07/13/2022

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

The free energy principle, and its corollary active inference, constitut...

0 Pietro Mazzaglia, et al. ∙

∙ 10/19/2021

Contrastive Active Inference

Active inference is a unifying theory for perception and action resting ...

0 Pietro Mazzaglia, et al. ∙

∙ 04/22/2021

A learning gap between neuroscience and reinforcement learning

Historically, artificial intelligence has drawn much inspiration from ne...

0 Samuel T. Wauthier, et al. ∙

∙ 04/15/2021

Self-Supervised Exploration via Latent Bayesian Surprise

Training with Reinforcement Learning requires a reward function that is ...

0 Pietro Mazzaglia, et al. ∙

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