Results 1 to 10 of about 1,036,354 (257)
Stratified Graphical Models - Context-Specific Independence in Graphical Models
Bayesian Analysis, 2013 Theory of graphical models has matured over more than three decades to provide the backbone for several classes of models that are used in a myriad of applications such as genetic mapping of diseases, credit risk evaluation, reliability and computer ...
Corander, Jukka +3 more
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Graphical Markov models: overview [PDF]
, 2015 We describe how graphical Markov models started to emerge in the last 40 years, based on three essential concepts that had been developed independently more than a century ago.
Andersen +73 more
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Conditional Functional Graphical Models. [PDF]
J Am Stat Assoc, 2023 Graphical modeling of multivariate functional data is becoming increasingly important in a wide variety of applications. The changes of graph structure can often be attributed to external variables, such as the diagnosis status or time, the latter of which gives rise to the problem of dynamic graphical modeling.
Lee KY, Ji D, Li L, Constable T, Zhao H.
europepmc +3 more sources
PU-GAT: Point cloud upsampling with graph attention network
Graphical Models, 2023 Point cloud upsampling has been extensively studied, however, the existing approaches suffer from the losing of structural information due to neglect of spatial dependencies between points.
Xuan Deng +3 more
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Unsupervised learning of style-aware facial animation from real acting performances
Graphical Models, 2023 This paper presents a novel approach for text/speech-driven animation of a photo-realistic head model based on blend-shape geometry, dynamic textures, and neural rendering.
Wolfgang Paier +2 more
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Fast progressive polygonal approximations for online strokes
Graphical Models, 2023 This paper presents a fast and progressive polygonal approximation algorithm for online strokes. A stroke is defined as a sequence of points between a pen-down and a pen-up. The proposed method generates polygonal approximations progressively as the user
Mohammad Tanvir Parvez
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Joint data and feature augmentation for self-supervised representation learning on point clouds
Graphical Models, 2023 To deal with the exhausting annotations, self-supervised representation learning from unlabeled point clouds has drawn much attention, especially centered on augmentation-based contrastive methods.
Zhuheng Lu +3 more
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RFMNet: Robust Deep Functional Maps for unsupervised non-rigid shape correspondence
Graphical Models, 2023 In traditional deep functional maps for non-rigid shape correspondence, estimating a functional map including high-frequency information requires enough linearly independent features via the least square method, which is prone to be violated in practice,
Ling Hu +5 more
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Unified shape and appearance reconstruction with joint camera parameter refinement
Graphical Models, 2023 In this paper, we present an inverse rendering method for the simple reconstruction of shape and appearance of real-world objects from only roughly calibrated RGB images captured under collocated point light illumination.
Julian Kaltheuner +2 more
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High-fidelity point cloud completion with low-resolution recovery and noise-aware upsampling
Graphical Models, 2023 Completing an unordered partial point cloud is a challenging task. Existing approaches that rely on decoding a latent feature to recover the complete shape, often lead to the completed point cloud being over-smoothing, losing details, and noisy.
Ren-Wu Li +4 more
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