Zobrazeno 1 - 10
of 155
pro vyhledávání: '"Vanhatalo, Jarno"'
Nutrient load simulators are large, deterministic, models that simulate the hydrodynamics and biogeochemical processes in aquatic ecosystems. They are central tools for planning cost efficient actions to fight eutrophication since they allow scenario
Externí odkaz:
http://arxiv.org/abs/2410.02448
Autor:
Ersalman, Murat, Kunnasranta, Mervi, Ahola, Markus, Carlsson, Anja M., Persson, Sara, Bäcklin, Britt-Marie, Helle, Inari, Cervin, Linnea, Vanhatalo, Jarno
Integrated population models (IPMs) are a promising approach to test ecological theories and assess wildlife populations in dynamic and uncertain conditions. By combining multiple data sources into a single, unified model, they enable the parametriza
Externí odkaz:
http://arxiv.org/abs/2408.08069
Species distribution models (SDMs) are key tools in ecology, conservation and management of natural resources. They are commonly trained by scientific survey data but, since surveys are expensive, there is a need for complementary sources of informat
Externí odkaz:
http://arxiv.org/abs/2206.08817
Joint species distribution models (JSDM) are among the most important statistical tools in community ecology. They are routinely used for inference and various prediction tasks, such as to build species distribution maps or biomass estimation over sp
Externí odkaz:
http://arxiv.org/abs/2111.02460
Ecological processes may exhibit memory to past disturbances affecting the resilience of ecosystems to future disturbance. Understanding the role of ecological memory in shaping ecosystem responses to disturbance under global change is a critical ste
Externí odkaz:
http://arxiv.org/abs/1902.07706
Autor:
Foster, Scott D., Vanhatalo, Jarno, Trenkel, Verena M., Schulz, Torsti, Lawrence, Emma, Przeslawski, Rachel, Hosack, Geoffrey R.
Publikováno v:
Ecological Applications, 2021 Sep 01. 31(6), 1-8.
Externí odkaz:
https://www.jstor.org/stable/27092182
Species distribution models (SDM) are a key tool in ecology, conservation and management of natural resources. Two key components of the state-of-the-art SDMs are the description for species distribution response along environmental covariates and th
Externí odkaz:
http://arxiv.org/abs/1809.02432
Autor:
Liu, Jia, Vanhatalo, Jarno
Publikováno v:
Spatial Statistics, 35:100392 (2020)
In geostatistics, the design for data collection is central for accurate prediction and parameter inference. One important class of geostatistical models is log-Gaussian Cox process (LGCP) which is used extensively, for example, in ecology. However,
Externí odkaz:
http://arxiv.org/abs/1808.09200
Autor:
Hartmann, Marcelo, Vanhatalo, Jarno
Publikováno v:
Statistics and Computing 2018
This paper considers the Laplace method to derive approximate inference for the Gaussian process (GP) regression in the location and scale parameters of the Student-t probabilistic model. This allows both mean and variance of the data to vary as a fu
Externí odkaz:
http://arxiv.org/abs/1712.07437
Publikováno v:
2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP)
Bayesian optimization (BO) is a global optimization strategy designed to find the minimum of an expensive black-box function, typically defined on a compact subset of $\mathcal{R}^d$, by using a Gaussian process (GP) as a surrogate model for the obje
Externí odkaz:
http://arxiv.org/abs/1704.00963