Discrete sampling data is used in several environmental studies to create maps in order to support decision-making processes. The decision maps represent an increasing importance i...
Compressed sensing is a new area of signal processing. Its goal is to minimize the number of samples that need to be taken from a signal for faithful reconstruction. The performan...
The problem of noise in Monte-Carlo rendering arising from estimator variance is well-known and well-studied. In this work, we concentrate on identifying individual light paths as...
Christopher DeCoro, Tim Weyrich, Szymon Rusinkiewi...
We are interested in computing tail probabilities for the maxima of Gaussian random fields. In this paper, we discuss two special cases: random fields defined over a finite number...
Active learning aims to reduce the amount of labels required for classification. The main difficulty is to find a good trade-off between exploration and exploitation of the lab...