Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Fabian Hadiji"'
Publikováno v:
An Introduction to Lifted Probabilistic Inference ISBN: 9780262365598
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c263bf4a2575705b4880e1c7ec68f591
https://doi.org/10.7551/mitpress/10548.003.0018
https://doi.org/10.7551/mitpress/10548.003.0018
Autor:
Fabian Hadiji, Inchon Hwang, Dae-Wook Kim, Eunjo Lee, Ji-Yeon Lee, Youngjun Joo, Jihoon Jeon, Anna Guitart, Pei Pei Chen, Marc Müller, Kyung-Joong Kim, Du-Mim Yoon, Yoonjae Jang, Paul Bertens, Seong-Il Yang, Sang-Kwang Lee, África Periáñez
Publikováno v:
arXiv
Game companies avoid sharing their game data with external researchers. Only a few research groups have been granted limited access to game data so far. The reluctance of these companies to make data publicly available limits the wide use and develop
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5f35b5efe848bcccf7a40214287177e4
https://doi.org/10.1109/tg.2018.2888863
https://doi.org/10.1109/tg.2018.2888863
Autor:
Georgios Mavromanolakis, Line Ebdrup Thomsen, Eleftherios Anastasovitis, Ioannis Kompatsiaris, Fabian Hadiji, Panagiotis Migkotzidis, Dimitrios Ververidis, Spiros Nikolopoulos, Marc Müller
Publikováno v:
The Challenges of the Digital Transformation in Education ISBN: 9783030119317
Online virtual labs, emulate real laboratories where students can accomplish a number of learning tasks and receive courses that otherwise would be difficult if not infeasible to be offered. In reaching this challenging goal, we developed two virtual
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e3582c5f87556d7fb703511bbc902e16
https://doi.org/10.1007/978-3-030-11932-4_66
https://doi.org/10.1007/978-3-030-11932-4_66
Publikováno v:
Transactions in GIS. 21:134-150
The automatic interpretation of 3D point clouds for building reconstruction is a challenging task. The interpretation process requires highly structured models representing semantics. Formal grammars can describe structures as well as the parameters
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2df069ee66dbae37572ecdf1cbccdc63
https://doi.org/10.1111/tgis.12200
https://doi.org/10.1111/tgis.12200
Publikováno v:
Interactive Collaborative Learning, 2018
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=r3c4b2081b22::bbc4548f25f7fec8213de0c286eff616
Publikováno v:
Machine Learning. 100:477-507
Although count data are increasingly ubiquitous, surprisingly little work has employed probabilistic graphical models for modeling count data. Indeed the univariate case has been well studied, however, in many situations counts influence each other a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aa9d8a591dd63eff9294bc3e8799da4f
https://doi.org/10.1007/s10994-015-5506-z
https://doi.org/10.1007/s10994-015-5506-z
Publikováno v:
BIBM
In order to facilitate better estimations on coronary artery disease conditions of a patient, we aim to predict the number of Angioplasty (a coronary artery procedure) by taking into account all the information from his/her Electronic Health Record (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d1e61d6a55255e1660f39d934c50b5c4
https://doi.org/10.1109/bibm.2017.8217696
https://doi.org/10.1109/bibm.2017.8217696
Autor:
Fabian Hadiji, Kristian Kersting
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 27:394-400
By handling whole sets of indistinguishable objects together, lifted belief propagation approaches have rendered large, previously intractable, probabilistic inference problems quickly solvable. In this paper, we show that Kumar and Zilberstein's lik
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::35a56025294eae0543d712a9503ea8ae
https://doi.org/10.1609/aaai.v27i1.8647
https://doi.org/10.1609/aaai.v27i1.8647
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 24:1181-1186
Lifted inference, handling whole sets of indistinguishable objects together, is critical to the effective application of probabilistic relational models to realistic real world tasks. Recently, lifted belief propagation (LBP) has been proposed as an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d7238d1a63ef63c3b9ecf9ea50e8cc07
https://doi.org/10.1609/aaai.v24i1.7759
https://doi.org/10.1609/aaai.v24i1.7759
Autor:
Lars Habel, Fabian Hadiji, Kristian Kersting, Alejandro Molina, Michael Schreckenberg, Thomas Zaksek, Christoph Ide, Christian Wietfeld
Publikováno v:
VTC Fall
The prediction of both, vehicular traffic and communication connectivity are important research topics. In this paper, we propose the usage of innovative machine learning approaches for these objectives. For this purpose, Poisson Dependency Networks
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::881ee8af5fa800574e02a9d0f406b965
https://doi.org/10.1109/vtcfall.2015.7391019
https://doi.org/10.1109/vtcfall.2015.7391019