Zobrazeno 1 - 10
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pro vyhledávání: '"A Alliez"'
Autor:
Éric Alliez
In seinem Notizbuchbeitrag überträgt der Philosoph Éric Alliez Überlegungen seines im Entstehen begriffenen Buchprojekts zur Diagrammatik und deren Implikationen für den Bereich der zeitgenössischen Kunst visuell auf die Gestalt des Textes selb
Bayesian Optimal Experimental Design (BOED) is a powerful tool to reduce the cost of running a sequence of experiments. When based on the Expected Information Gain (EIG), design optimization corresponds to the maximization of some intractable expecte
Externí odkaz:
http://arxiv.org/abs/2410.11826
We present a novel approach for generating isotropic surface triangle meshes directly from unoriented 3D point clouds, with the mesh density adapting to the estimated local feature size (LFS). Popular reconstruction pipelines first reconstruct a dens
Externí odkaz:
http://arxiv.org/abs/2403.13924
Although polygon meshes have been a standard representation in geometry processing, their irregular and combinatorial nature hinders their suitability for learning-based applications. In this work, we introduce a novel learnable mesh representation t
Externí odkaz:
http://arxiv.org/abs/2403.12870
Autor:
Pascale Cassagnau
Publikováno v:
Chimères. :243-246
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed4b76b6b627380158501afcf7a38ebd
https://doi.org/10.3917/chime.102.0243
https://doi.org/10.3917/chime.102.0243
Publikováno v:
Proceedings of the 41st International Conference on Machine Learning, 2024
We propose a new procedure named PASOA, for Bayesian experimental design, that performs sequential design optimization by simultaneously providing accurate estimates of successive posterior distributions for parameter inference. The sequential design
Externí odkaz:
http://arxiv.org/abs/2402.07160
Autor:
Louise Boisclair
Publikováno v:
Recensions. :157-161
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d78c18ae00b6f3ec5136f7151e8e5f69
https://doi.org/10.7202/1090766ar
https://doi.org/10.7202/1090766ar
Autor:
Gherasim-Proca, Ovidiu
Publikováno v:
Psihologia socială / Social Psychology. 1(39):103-105
Externí odkaz:
https://www.ceeol.com/search/article-detail?id=610412
In stark contrast to the case of images, finding a concise, learnable discrete representation of 3D surfaces remains a challenge. In particular, while polygon meshes are arguably the most common surface representation used in geometry processing, the
Externí odkaz:
http://arxiv.org/abs/2308.14616
This paper proposes BPNet, a novel end-to-end deep learning framework to learn B\'ezier primitive segmentation on 3D point clouds. The existing works treat different primitive types separately, thus limiting them to finite shape categories. To addres
Externí odkaz:
http://arxiv.org/abs/2307.04013