Michael Garcia Ortiz | DeepAI

DeepAI AI Chat

Featured Co-authors

David Filliat
32 publications
Timothée Lesort
23 publications
Alban Laflaquière
16 publications
Hugo Caselles-Dupré
15 publications
Andrei Stoian
7 publications
Eduardo Alonso
7 publications
Louis Annabi
7 publications
Thibaut Kulak
3 publications
Nikolas Hemion
2 publications
Vince Jankovics
1 publication
Jean-Christophe Baillie
1 publication

∙ 06/06/2022

Efficient entity-based reinforcement learning

Recent deep reinforcement learning (DRL) successes rely on end-to-end le...

0 Vince Jankovics, et al. ∙

∙ 07/05/2021

Are standard Object Segmentation models sufficient for Learning Affordance Segmentation?

Affordances are the possibilities of actions the environment offers to t...

0 Hugo Caselles-Dupré, et al. ∙

∙ 07/05/2021

SCOD: Active Object Detection for Embodied Agents using Sensory Commutativity of Action Sequences

We introduce SCOD (Sensory Commutativity Object Detection), an active me...

7 Hugo Caselles-Dupré, et al. ∙

∙ 02/13/2020

On the Sensory Commutativity of Action Sequences for Embodied Agents

We study perception in the scenario of an embodied agent equipped with f...

0 Hugo Caselles-Dupré, et al. ∙

∙ 06/04/2019

Unsupervised Emergence of Egocentric Spatial Structure from Sensorimotor Prediction

Despite its omnipresence in robotics application, the nature of spatial ...

0 Alban Laflaquière, et al. ∙

∙ 03/30/2019

Symmetry-Based Disentangled Representation Learning requires Interaction with Environments

Finding a generally accepted formal definition of a disentangled represe...

0 Hugo Caselles-Dupré, et al. ∙

∙ 02/25/2019

S-TRIGGER: Continual State Representation Learning via Self-Triggered Generative Replay

We consider the problem of building a state representation model for con...

22 Hugo Caselles-Dupré, et al. ∙

∙ 12/28/2018

State representation learning with recurrent capsule networks

Unsupervised learning of compact and relevant state representations has ...

0 Louis Annabi, et al. ∙

∙ 12/21/2018

Generative Models from the perspective of Continual Learning

Which generative model is the most suitable for Continual Learning? This...

16 Timothée Lesort, et al. ∙

∙ 10/09/2018

Continual State Representation Learning for Reinforcement Learning using Generative Replay

We consider the problem of building a state representation model in a co...

0 Hugo Caselles-Dupré, et al. ∙

∙ 10/03/2018

Grounding Perception: A Developmental Approach to Sensorimotor Contingencies

Sensorimotor contingency theory offers a promising account of the nature...

2 Alban Laflaquière, et al. ∙

∙ 09/03/2018

Flatland: a Lightweight First-Person 2-D Environment for Reinforcement Learning

We propose Flatland, a simple, lightweight environment for fast prototyp...

0 Hugo Caselles-Dupré, et al. ∙

∙ 05/16/2018

Learning Representations of Spatial Displacement through Sensorimotor Prediction

Robots act in their environment through sequences of continuous motor co...

0 Michael Garcia Ortiz, et al. ∙

∙ 03/01/2018

Representation Learning in Partially Observable Environments using Sensorimotor Prediction

In order to explore and act autonomously in an environment, an agent nee...

0 Thibaut Kulak, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world