4 citations · 6 across the 10 of their papers we have counts for
4 papers · 1 filter
EDO-Net: Learning Elastic Properties of Deformable Objects from Graph Dynamics
Alberta Longhini, Marco Moletta, Alfredo Reichlin +4
We study the problem of learning graph dynamics of deformable objects that generalizes to unknown physical properties. Our key insight is to leverage a latent representation of ela…
Elastic Context: Encoding Elasticity for Data-driven Models of Textiles
Alberta Longhini, Marco Moletta, Alfredo Reichlin +6
Physical interaction with textiles, such as assistive dressing, relies on advanced dextreous capabilities. The underlying complexity in textile behavior when being pulled and stret…
Back to the Manifold: Recovering from Out-of-Distribution States
Alfredo Reichlin, Giovanni Luca Marchetti, Hang Yin +2
Learning from previously collected datasets of expert data offers the promise of acquiring robotic policies without unsafe and costly online explorations. However, a major challeng…
On the Subspace Structure of Gradient-Based Meta-Learning
Gustaf Tegnér, Alfredo Reichlin, Hang Yin +2
In this work we provide an analysis of the distribution of the post-adaptation parameters of Gradient-Based Meta-Learning (GBML) methods. Previous work has noticed how, for the cas…