We offer a complete characterization of the set of distributions that could be induced by local interventions on variables governed by a causal Bayesian network of unknown structu...
Future collaborative learning technologies are characterized by the CSCL community as highly malleable and flexible. A promising approach for meeting these expectations is to use ...
Many activity dependent learning rules have been proposed in order to model long-term potentiation (LTP). Our aim is to derive a spike time dependent learning rule from a probabili...
Jean-Pascal Pfister, David Barber, Wulfram Gerstne...
This poster describes a framework that automatically generates learning support scaffolds to guide task-based learning. The aim is to combine the exploratory learning principles p...
— We present an algorithm for learning 3D object models from partial object observations. The input to our algorithm is a sequence of 3D laser range scans. Models learned from th...
Michael Ruhnke, Bastian Steder, Giorgio Grisetti, ...