15 citations · 30 across the 10 of their papers we have counts for
6 papers · 1 filter
Privacy-Aware Lifelong Learning
Ozan Özdenizci, Elmar Rueckert, Robert Legenstein
Lifelong learning algorithms enable models to incrementally acquire new knowledge without forgetting previously learned information. Contrarily, the field of machine unlearning foc…
ED-VAE: Entropy Decomposition of ELBO in Variational Autoencoders
Fotios Lygerakis, Elmar Rueckert
Traditional Variational Autoencoders (VAEs) are constrained by the limitations of the Evidence Lower Bound (ELBO) formulation, particularly when utilizing simplistic, non-analytic,…
CR-VAE: Contrastive Regularization on Variational Autoencoders for Preventing Posterior Collapse
Fotios Lygerakis, Elmar Rueckert
The Variational Autoencoder (VAE) is known to suffer from the phenomenon of \textit{posterior collapse}, where the latent representations generated by the model become independent…
SKID RAW: Skill Discovery from Raw Trajectories
Daniel Tanneberg, Kai Ploeger, Elmar Rueckert +1
Integrating robots in complex everyday environments requires a multitude of problems to be solved. One crucial feature among those is to equip robots with a mechanism for teaching…
Experience Reuse with Probabilistic Movement Primitives
Svenja Stark, Jan Peters, Elmar Rueckert
Acquiring new robot motor skills is cumbersome, as learning a skill from scratch and without prior knowledge requires the exploration of a large space of motor configurations. Acco…
Learning walk and trot from the same objective using different types of exploration
Zinan Liu, Kai Ploeger, Svenja Stark +2
In quadruped gait learning, policy search methods that scale high dimensional continuous action spaces are commonly used. In most approaches, it is necessary to introduce prior kno…