Zobrazeno 1 - 10
of 86
pro vyhledávání: '"Thomas D. NIELSEN"'
Autor:
Guohan Zhao, Michael R. Rasmussen, Kim G. Larsen, Jiri Srba, Thomas D. Nielsen, Martijn A. Goorden, Weizhu Qian, Jesper E. Nielsen
Publikováno v:
Journal of Hydroinformatics, Vol 25, Iss 4, Pp 1256-1275 (2023)
Flow-regulated stormwater ponds providing safe outflow discharges prevail as the primary stormwater management tool for stream protections. Detailed pond geometries are essential metrics in pond monitoring technologies, which convert the point-based
Externí odkaz:
https://doaj.org/article/3b0ce51ddc6045298ea815e8a9c86a5a
Publikováno v:
Entropy, Vol 23, Iss 1, p 117 (2021)
Recent advances in statistical inference have significantly expanded the toolbox of probabilistic modeling. Historically, probabilistic modeling has been constrained to very restricted model classes, where exact or approximate probabilistic inference
Externí odkaz:
https://doaj.org/article/57c0bd55a4bc400e96dd46e4fd23f0b2
Publikováno v:
Mathematics, Vol 8, Iss 11, p 1942 (2020)
In many modern data analysis problems, the available data is not static but, instead, comes in a streaming fashion. Performing Bayesian inference on a data stream is challenging for several reasons. First, it requires continuous model updating and th
Externí odkaz:
https://doaj.org/article/41eb600d6b594db7a081d54480136171
Publikováno v:
Electronic Proceedings in Theoretical Computer Science, Vol 103, Iss Proc. QFM 2012, Pp 49-63 (2012)
Constructing an accurate system model for formal model verification can be both resource demanding and time-consuming. To alleviate this shortcoming, algorithms have been proposed for automatically learning system models based on observed system beha
Externí odkaz:
https://doaj.org/article/af821cf6d2e644648f342f591e57800f
Autor:
Siska BJØRN, Thomas D. NIELSEN, Anne E. JENSEN, Christian JESSEN, Jens A. KOLSEN-PETERSEN, Bernhard MORIGGL, Romed HOERMANN, Jens R. NYENGAARD, Thomas F. BENDTSEN
Publikováno v:
Bjørn, S, Nielsen, T D, Jensen, A E, Jessen, C, Petersen, J A K, Moriggl, B, Hoermann, R, Nyengaard, J R & Bendtsen, T F 2023, ' The anterior branch of the medial femoral cutaneous nerve innervates the anterior knee: a randomized volunteer trial ', Minerva Anestesiologica . https://doi.org/10.23736/s0375-9393.22.16910-5
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4ff44bb37c11716d6f57152b9fe44193
https://pure.au.dk/portal/da/publications/the-anterior-branch-of-the-medial-femoral-cutaneous-nerve-innervates-the-anterior-knee-a-randomized-volunteer-trial(8aa9bc89-228b-46ea-85f8-f895e49e91f8).html
https://pure.au.dk/portal/da/publications/the-anterior-branch-of-the-medial-femoral-cutaneous-nerve-innervates-the-anterior-knee-a-randomized-volunteer-trial(8aa9bc89-228b-46ea-85f8-f895e49e91f8).html
Publikováno v:
Bruun, A, Law, E L C, Nielsen, T D & Heintz, M 2021, ' Do You Feel the Same? On the Robustness of Cued-Recall Debriefing for User Experience Evaluation ', ACM Transactions on Computer-Human Interaction, vol. 28, no. 4, 25, pp. 1-45 . https://doi.org/10.1145/3453479
Cued Recall Debriefing (CRD) is a form of retrospective think aloud approach. It involves re-immersing users to a level where emotional responses are comparable to those experienced during actual interaction with a system. To validate whether the rob
Publikováno v:
Frazzetto, D, Nielsen, T D, Pedersen, T B & Siksnys, L 2019, ' Prescriptive Analytics : A Survey of Emerging Trends And Technologies ', V L D B Journal, vol. 28, no. 4, pp. 575-595 . https://doi.org/10.1007/s00778-019-00539-y
This paper provides a survey of the state-of-the-art and future directions of one of the most importantemerging technologies within Business Analytics(BA), namely Prescriptive Analytics (PSA). BA focuseson data-driven decision making and consists oft
Autor:
Martijn A. Goorden, Jiri Srba, Kim Guldstrand Larsen, Thomas D. Nielsen, Jesper Ellerbæk Nielsen, Michael R. Rasmussen
Publikováno v:
ADHS
IFAC-PapersOnLine : 7th IFAC Conference on Analysis and Design of Hybrid Systems
IFAC-PapersOnLine : 7th IFAC Conference on Analysis and Design of Hybrid Systems
Storm water detention ponds are used to manage the discharge of rainfall runoff from urban areas to nearby streams. Their purpose is to reduce the hydraulic impact and sediment loads of the receiving waters. Detention ponds are currently designed bas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2259cf7fc50bbc43a3f90b2290a4a573
http://arxiv.org/abs/2104.12509
http://arxiv.org/abs/2104.12509
Publikováno v:
Masegosa, A, Cabañas, R, Langseth, H, Nielsen, T D & Salmerón, A 2021, ' Probabilistic Models with Deep Neural Networks ', Entropy, vol. 23, no. 1, 117, pp. 1-27 . https://doi.org/10.3390/e23010117, https://doi.org/10.3390/e23010117
Entropy
riUAL. Repositorio Institucional de la Universidad de Almería
Universidad de Almería
Entropy, Vol 23, Iss 117, p 117 (2021)
Entropy
riUAL. Repositorio Institucional de la Universidad de Almería
Universidad de Almería
Entropy, Vol 23, Iss 117, p 117 (2021)
Recent advances in statistical inference have significantly expanded the toolbox of probabilistic modeling. Historically, probabilistic modeling has been constrained to very restricted model classes, where exact or approximate probabilistic inference
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::82a2f350865fed69830a9766f85e9f47
https://vbn.aau.dk/ws/files/457949814/entropy_23_00117_v2.pdf
https://vbn.aau.dk/ws/files/457949814/entropy_23_00117_v2.pdf
Publikováno v:
Masegosa, A R, Ramos-López, D, Cerdán, A S, Langseth, H & Nielsen, T D 2020, ' Variational Inference over Nonstationary Data Streams for Exponential Family Models ', Mathematics, vol. 8, no. 11, 1942, pp. 1-27 . https://doi.org/10.3390/math8111942
Mathematics, Vol 8, Iss 1942, p 1942 (2020)
Mathematics
Mathematics; Volume 8; Issue 11; Pages: 1942
Mathematics, Vol 8, Iss 1942, p 1942 (2020)
Mathematics
Mathematics; Volume 8; Issue 11; Pages: 1942
In many modern data analysis problems, the available data is not static but, instead, comes in a streaming fashion. Performing Bayesian inference on a data stream is challenging for several reasons. First, it requires continuous model updating and th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::61de0489ef5fd570a218b047d48ded2c
https://vbn.aau.dk/ws/files/392340157/mathematics_08_01942_v2.pdf
https://vbn.aau.dk/ws/files/392340157/mathematics_08_01942_v2.pdf