9 citations · 12 across the 3 of their papers we have counts for
3 papers
Towards Compute-Optimal Transfer Learning
Massimo Caccia, Alexandre Galashov, Arthur Douillard +6
The field of transfer learning is undergoing a significant shift with the introduction of large pretrained models which have demonstrated strong adaptability to a variety of downst…
Leveraging Jumpy Models for Planning and Fast Learning in Robotic Domains
Jingwei Zhang, Jost Tobias Springenberg, Arunkumar Byravan +5
In this paper we study the problem of learning multi-step dynamics prediction models (jumpy models) from unlabeled experience and their utility for fast inference of (high-level) p…
Incorporating Human Domain Knowledge into Large Scale Cost Function Learning
Markus Wulfmeier, Dushyant Rao, Ingmar Posner
Recent advances have shown the capability of Fully Convolutional Neural Networks (FCN) to model cost functions for motion planning in the context of learning driving preferences pu…