4 citations · 11 across the 8 of their papers we have counts for
8 papers
MILES: Making Imitation Learning Easy with Self-Supervision
Georgios Papagiannis, Edward Johns
Data collection in imitation learning often requires significant, laborious human supervision, such as numerous demonstrations, and/or frequent environment resets for methods that…
Adapting Skills to Novel Grasps: A Self-Supervised Approach
Georgios Papagiannis, Kamil Dreczkowski, Vitalis Vosylius +1
In this paper, we study the problem of adapting manipulation trajectories involving grasped objects (e.g. tools) defined for a single grasp pose to novel grasp poses. A common appr…
R+X: Retrieval and Execution from Everyday Human Videos
Georgios Papagiannis, Norman Di Palo, Pietro Vitiello +1
We present R+X, a framework which enables robots to learn skills from long, unlabelled, first-person videos of humans performing everyday tasks. Given a language command from a hum…
Demonstrate Once, Imitate Immediately (DOME): Learning Visual Servoing for One-Shot Imitation Learning
Eugene Valassakis, Georgios Papagiannis, Norman Di Palo +1
We present DOME, a novel method for one-shot imitation learning, where a task can be learned from just a single demonstration and then be deployed immediately, without any further…
End-To-End Semi-supervised Learning for Differentiable Particle Filters
Hao Wen, Xiongjie Chen, Georgios Papagiannis +2
Recent advances in incorporating neural networks into particle filters provide the desired flexibility to apply particle filters in large-scale real-world applications. The dynamic…
Imitation Learning with Sinkhorn Distances
Georgios Papagiannis, Yunpeng Li
Imitation learning algorithms have been interpreted as variants of divergence minimization problems. The ability to compare occupancy measures between experts and learners is cruci…
Deep Reinforcement Learning for Control of Probabilistic Boolean Networks
Georgios Papagiannis, Sotiris Moschoyiannis
Probabilistic Boolean Networks (PBNs) were introduced as a computational model for the study of complex dynamical systems, such as Gene Regulatory Networks (GRNs). Controllability…
A Bayesian Ensemble Regression Framework on the Angry Birds Game
Nikolaos Tziortziotis, Georgios Papagiannis, Konstantinos Blekas
An ensemble inference mechanism is proposed on the Angry Birds domain. It is based on an efficient tree structure for encoding and representing game screenshots, where it exploits…