… In this work, we sketch a graphical model in a small space. … P factors according to a known
graphical model \(\mathcal {G}\)… to the MLE in graphical models with high-cardinality variables. …

… learning-based face sketch synthesis models stacked only by … graphical model and propose
a novel face sketch synthesis framework based on the neural probabilistic graphical model (…

… want to model the distribution over the weights for deep patch representation. So, we design
a graphical model based deep patch representation learning framework to jointly model the …

… graphical models. Therefore, we describe our models using a class of probabilistic graphical
models known … DBNs have successfully been used to model time series, and are therefore …

… : to create a 3D model, to add details to an existing model, or to deform and manipulate a
model. Additionally, in this paper we introduce a survey of sketch-based interfaces focused on …

… sketch patches into a whole synthesized sketch with overlapping area averaged. Because
our probabilistic graphical model … the overlapping patches could generate a seamless sketch. …

… Graphical model structure learnt from top-down detected features for 40 CEs; background …
Using the graphical models of this section instead of the naive-Bayes ones used earlier for the …

… a sequence of U curve strokes Φ(0),Φ(1),...,Φ(U), a set S of N curve refinement models Λ0
… graph Λ1, we wish to determine the most likely sequence of curve-level refinement models …

… In this article, we present our sketch-recognition framework, … people sketch and then use the
orderings for sketch recognition… We also present an efficient graphical model implementation …

… we present builds 3D models from handdrawn sketches. To … and our sketch recognition does
not require graph connectivity … the strokes of an input sketch and the resulting sketch graph. …