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07/18/2022
Back to the Manifold: Recovering from Out-of-Distribution States
Learning from previously collected datasets of expert data offers the pr...
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04/18/2022
Training and Evaluation of Deep Policies using Reinforcement Learning and Generative Models
We present a data-efficient framework for solving sequential decision-ma...
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03/05/2021
Bayesian Meta-Learning for Few-Shot Policy Adaptation Across Robotic Platforms
Reinforcement learning methods can achieve significant performance but r...
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10/16/2020
Few-shot model-based adaptation in noisy conditions
Few-shot adaptation is a challenging problem in the context of simulatio...
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07/26/2020
Data-efficient visuomotor policy training using reinforcement learning and generative models
We present a data-efficient framework for solving deep visuomotor sequen...
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07/02/2020
Human-centered collaborative robots with deep reinforcement learning
We present a reinforcement learning based framework for human-centered c...
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10/14/2019
Imitating by generating: deep generative models for imitation of interactive tasks
To coordinate actions with an interaction partner requires a constant ex...
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09/17/2019
Adversarial Feature Training for Generalizable Robotic Visuomotor Control
Deep reinforcement learning (RL) has enabled training action-selection p...
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09/16/2019
Meta Reinforcement Learning for Sim-to-real Domain Adaptation
Modern reinforcement learning methods suffer from low sample efficiency ...
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03/10/2019
Affordance Learning for End-to-End Visuomotor Robot Control
Training end-to-end deep robot policies requires a lot of domain-, task-...
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02/04/2019
Exploring Temporal Dependencies in Multimodal Referring Expressions with Mixed Reality
In collaborative tasks, people rely both on verbal and non-verbal cues s...
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11/08/2018
Meta-Learning for Multi-objective Reinforcement Learning
Multi-objective reinforcement learning (MORL) is the generalization of s...
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04/27/2018
