Hugo Caselles-Dupré | DeepAI

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∙ 09/26/2022

Overcoming Referential Ambiguity in Language-Guided Goal-Conditioned Reinforcement Learning

Teaching an agent to perform new tasks using natural language can easily...

0 Hugo Caselles-Dupré, et al. ∙

∙ 06/09/2022

Pragmatically Learning from Pedagogical Demonstrations in Multi-Goal Environments

Learning from demonstration methods usually leverage close to optimal de...

0 Hugo Caselles-Dupré, et al. ∙

∙ 02/28/2022

Pedagogical Demonstrations and Pragmatic Learning in Artificial Tutor-Learner Interactions

When demonstrating a task, human tutors pedagogically modify their behav...

0 Hugo Caselles-Dupré, 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. ∙

∙ 05/25/2021

Towards Teachable Autonomous Agents

Autonomous discovery and direct instruction are two extreme sources of l...

10 Olivier Sigaud, 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. ∙

∙ 07/11/2019

DisCoRL: Continual Reinforcement Learning via Policy Distillation

In multi-task reinforcement learning there are two main challenges: at t...

6 René Traoré, et al. ∙

∙ 06/11/2019

Continual Reinforcement Learning deployed in Real-life using Policy Distillation and Sim2Real Transfer

We focus on the problem of teaching a robot to solve tasks presented seq...

0 René Traoré, 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. ∙

∙ 12/21/2018

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. ∙

∙ 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. ∙

∙ 04/11/2018

Word2Vec applied to Recommendation: Hyperparameters Matter

Skip-gram with negative sampling, a popular variant of Word2vec original...

0 Hugo Caselles-Dupré, et al. ∙

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