output
20092025
most citedActive Learning of Inverse Models with Intrinsically Motivated Goal Exploration in Robots

451 citations

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9 papers · 1 filter

cs.LG2025

Torch-Uncertainty: A Deep Learning Framework for Uncertainty Quantification

Adrien Lafage, Olivier Laurent, Firas Gabetni +1

Deep Neural Networks (DNNs) have demonstrated remarkable performance across various domains, including computer vision and natural language processing. However, they often struggle…

cs.LG2019★ 15 cited

Symmetry-Based Disentangled Representation Learning requires Interaction with Environments

Hugo Caselles-Dupré, Michael Garcia-Ortiz, David Filliat

Finding a generally accepted formal definition of a disentangled representation in the context of an agent behaving in an environment is an important challenge towards the construc…

cs.LG2018★ 5 cited

Diversity-Driven Selection of Exploration Strategies in Multi-Armed Bandits

Fabien C. Y. Benureau, Pierre-Yves Oudeyer

We consider a scenario where an agent has multiple available strategies to explore an unknown environment. For each new interaction with the environment, the agent must select whic…

cs.LG2018★ 12 cited

Training Discriminative Models to Evaluate Generative Ones

Timothée Lesort, Andrei Stoain, Jean-François Goudou +1

Generative models are known to be difficult to assess. Recent works, especially on generative adversarial networks (GANs), produce good visual samples of varied categories of image…

cs.LG2018★ 56 cited

Active choice of teachers, learning strategies and goals for a socially guided intrinsic motivation learner

Sao Mai Nguyen, Pierre-Yves Oudeyer

We present an active learning architecture that allows a robot to actively learn which data collection strategy is most efficient for acquiring motor skills to achieve multiple out…

cs.LG2016★ 1 cited

A simple technique for improving multi-class classification with neural networks

Thomas Kopinski, Alexander Gepperth, Uwe Handmann

We present a novel method to perform multi-class pattern classification with neural networks and test it on a challenging 3D hand gesture recognition problem. Our method consists o…