Results 231 to 240 of about 43,983 (273)

Habitat complexity and prey composition shape an apex predator's habitat use across contrasting landscapes

Ecography, EarlyView.
The spatial ecology of stalk‐and‐ambush predators like the Eurasian lynx Lynx lynx depends on prey availability and environmental features, yet the relative roles of these factors remain unclear at large spatial scales. In this study, we analysed lynx habitat use across central and southern Finland using snow‐track data from the Wildlife Triangle ...
Francesca Malcangi, Caio Graco‐Roza, Andreas Lindén, Janne Sundell, John Loehr   +4 more
wiley   +1 more source

A Review of R Packages for Bayesian Model-based Clustering of High-dimensional Multivariate Environmental Exposures. [PDF]

Curr Environ Health Rep
Stephenson BJK, Fu Y.
europepmc   +1 more source

Harnessing the power of machine and deep learning for transferring joint species distribution models considering the structure of biotic interactions

Ecography, EarlyView.
The transferability of single or joint species distribution models ((j)SDMs) depends on their ability to predict beyond the observed environmental range and to remain consistent despite shifts in biotic interactions. Transfer accuracy may be improved by recent advances in the application of deep learning that provide greater flexibility and potentially
Marco Basile, Maximilian Pichler, Francesco Valerio, Lorenzo Balducci, Francesco Chianucci, Sérgio Godinho, Francesco Rota, Frédéric Archaux, Christophe Bouget, Gediminas Brazaitis, Thomas Campagnaro, Ettore D'Andrea, Luc De Keersmaeker, Wouter Dekoninck, Pallieter De Smedt, Zoltán Elek, Itziar García‐ Mijangos, Frédéric Gosselin, Marion Gosselin, Andrin Gross, Elena Haeler, Sebastian Kepfer‐ Rojas, Nathalie Korboulewsky, Daniel Kozák, Thibault Lachat, Carlos Miguel Landivar Albis, Anja Leyman, Xiang Liu, Anders Mårell, Radim Matula, Martin Mikoláš, Péter Ódor, Yoan Paillet, Kastytis Šimkevičius, Tommaso Sitzia, Silvia Stofer, Nicolas Strebel, Miroslav Svoboda, Flóra Tinya, Mariana Ujházyová, Kris Vandekerkhove, Kris Verheyen, Michael Wohlwend, Fotios Xystrakis, Sabina Burrascano   +44 more
wiley   +1 more source

Deep representation learning for temporal inference in cancer omics: a systematic literature review. [PDF]

Brief Bioinform
Prol-Castelo G, Cirillo D, Valencia A.
europepmc   +1 more source

Gradient-Free De Novo Learning. [PDF]

Entropy (Basel)
Friston K, Parr T, Heins C, Da Costa L, Salvatori T, Tschantz A, Koudahl M, Van de Maele T, Buckley C, Verbelen T.   +9 more
europepmc   +1 more source

A primer on variational inference for physics-informed deep generative modelling. [PDF]

Philos Trans A Math Phys Eng Sci
Glyn-Davies A, Vadeboncoeur A, Akyildiz OD, Kazlauskaite I, Girolami M.   +4 more
europepmc   +1 more source

Deep Mixture of Linear Mixed Models for Complex Longitudinal Data. [PDF]

Stat Med
Kock L, Klein N, Nott DJ.
europepmc   +1 more source

Collapsed Variational Bayesian Inference for Hidden Markov Models.

, 2016
Wang, P, Blunsom, P
openaire   +3 more sources