Automated Model Inference for Gaussian Processes

Autor: Berns, F., Hüwel, J., Beecks, C.

Gaussian process models (GPMs) are widely regarded as a prominent tool for learning statistical data models that enable interpolation, regression, and classification. These models are typically instantiated by a Gaussian Process with a zero-mean func

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______610::7b567c7add02f15de979690b9e6d8a1f
https://publica.fraunhofer.de/handle/publica/428501

Automated Model Inference for Gaussian Processes: An Overview of State-of-the-Art Methods and Algorithms.

Autor: Berns F; University of Hagen, Hagen, Germany., Hüwel J; University of Hagen, Hagen, Germany., Beecks C; University of Hagen, Hagen, Germany.; Fraunhofer Institute for Applied Information Technology FIT, Sankt Augustin, Germany.

Publikováno v: SN computer science [SN Comput Sci] 2022; Vol. 3 (4), pp. 300. Date of Electronic Publication: 2022 May 21.

Collaborative Video Search Combining Video Retrieval with Human-Based Visual Inspection

Autor: Hudelist, M.A., Cobârzan, C., Beecks, C., van de Werken, Rob, Kletz, S., Hürst, W.O., Schoeffmann, K., Sub Multimedia, Multimedia

Publikováno v: MultiMedia Modeling ISBN: 9783319276731
MMM (2)
MultiMedia Modeling, 2, 400. Springer

We propose a novel video browsing approach that aims at optimally integrating traditional, machine-based retrieval methods with an interface design optimized for human browsing performance. Advanced video retrieval and filtering (e.g., via color and

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ab521f31670757f1d6e92872cf1da9d6
https://doi.org/10.1007/978-3-319-27674-8_40

Deep Kernel learning for reaction outcome prediction and optimization.

Autor: Singh, Sukriti¹ (AUTHOR) sukriti243@gmail.com, Hernández-Lobato, José Miguel¹ (AUTHOR) jmh233@cam.ac.uk

Publikováno v: Communications Chemistry. 6/14/2024, Vol. 7 Issue 1, p1-9. 9p.

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