This paper contains two important contributions for the development of possibilistic causal networks. The first one concerns the representation of interventions in possibilistic ...
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
This paper describes a car traffic control simulation realised in a decentralised way by message propagations: congested nodes (roads intersections) send speed-up or slow-down mess...
In this paper, we propose a new algorithm for the fundamental problem of reconstructing surfaces from a large set of unorganized 3D data points. The local shapes of the surface ar...
We presenthere an approachand algorithm for mining generalizedterm associations.The problem is to find co-occurrencefrequenciesof terms, given a collection of documents eachwith r...
Jonghyun Kahng, Wen-Hsiang Kevin Liao, Dennis McLe...