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Št. zadetkov: 30
COLOSS survey: global impact of COVID-19 on bee research
Raffaele Dall'Olio, Tjeerd Blacquière, Maria Bouga, Robert Brodschneider, Norman L. Carreck, Panuwan Chantawannakul, Vincent Dietemann, Lotta Fabricius Kristiansen, Anna M. Gajda, Aleš Gregorc, Asli Ozkirim, Christian Pirk, Victoria Soroker, Geoffrey R. Williams, Peter Neumann
Izvirni znanstveni članek
Oznake: COLOSS;Apis mellifera;coronavirus;COVID-19;honey bee;pandemic;research;extension;
The socio-economic impacts of COVID-19 on society have yet to be truly revealed; there is no doubt that the pandemic has severely affected the daily lives of most of humanity. It is to be expected that the research activities of scientists could be impacted to varying degrees, but no data exist on h ...
Leto: 2020 Vir: Fakulteta za kmetijstvo in biosistemske vede (UM FKBV)
Supplementary material for paper COLOSS survey: global impact of COVID-19 on bee research
Raffaele Dall'Olio, Tjeerd Blacquière, Maria Bouga, Robert Brodschneider, Norman L. Carreck, Panuwan Chantawannakul, Victoria Soroker, Geoffrey R. Williams, Peter Neumann, Vincent Dietemann, Lotta Fabricius Kristiansen, Anna M. Gajda, Aleš Gregorc, Asli Ozkirim, Christian Pirk
Raziskovalni podatki
Oznake: COLOSS;Apis mellifera;coronavirus;COVID-19;honey bee;pandemic;research;extension;
The socio-economic impacts of COVID-19 on society have yet to be truly revealed; there is no doubt that the pandemic has severely affected the daily lives of most of humanity. It is to be expected that the research activities of scientists could be impacted to varying degrees, but no data exist on h ...
Leto: 2020 Vir: Fakulteta za kmetijstvo in biosistemske vede (UM FKBV)
Self-mapping Networks
Geoffrey Canright
Video in druga učna gradiva
Oznake: computer science;network analysis;mathematics;graph theory
Leto: 2007 Vir: videolectures.net
Topographic Analysis of an Empirical Human Sexual Network
Geoffrey Canright
Video in druga učna gradiva
Oznake: computer science;network analysis;social networks
Spreading of electronic viruses, among computers and mobile phones, typically depends on address/phone number lists. The network formed by these lists is not symmetric: the fact that A has B’s address does not ensure that B has A’s address. Thus the underlying network on which such spreading takes p ...
Leto: 2007 Vir: videolectures.net
Weka, MOA and Experiment Databases: Frameworks for Machine Learning
Geoffrey Holmes
Video in druga učna gradiva
Oznake: computer science;machine learning
This talk is in three parts. The first deals with an aspect of the Weka project that has received little attention, namely the use of machine learning in agricultural applications. I will outline our experiences in this field and present an application development framework which is a direct result ...
Leto: 2013 Vir: videolectures.net
ǂThe ǂsomaesthetics of heaviness and Hara in Zen Buddhist meditation
Geoffrey Ashton
Izvirni znanstveni članek
Oznake: zazen;duḥkha;gravity;grief;somaesthetics;hara;breathing;
Breath is a grounding phenomenon present in many forms of Buddhist medi-tation. In traditional Buddhist meditations (including ānāpānasati and vipassanā), the practitioner observes the breath, surveys various physical and mental phenom-ena, and from there realizes that suffering (duḥkha) is not ulti ...
Leto: 2023 Vir: Univerza na Primorskem (UP)
Brain tumour migration and invasion
Geoffrey J. Pilkington
Strokovni članek
Oznake:
Leto: 2002 Vir: dLib.si Digitalna knjižnica Slovenije
No-Regret Learning in Convex Games
Geoffrey J. Gordon
Video in druga učna gradiva
Oznake: computer science;machine learning
Quite a bit is known about minimizing different kinds of regret in experts problems, and how these regret types relate to types of equilibria in the multiagent setting of repeated matrix games. Much less is known about the possible kinds of regret in online convex programming problems (OCPs), or abo ...
Leto: 2008 Vir: videolectures.net
A tutorial on Deep Learning
Geoffrey E. Hinton
Video in druga učna gradiva
Oznake: computer science;machine learning
Complex probabilistic models of unlabeled data can be created by combining simpler models. Mixture models are obtained by averaging the densities of simpler models and "products of experts" are obtained by multiplying the densities together and renormalizing. A far more powerful type of combination ...
Leto: 2009 Vir: videolectures.net
Deep Belief Networks
Geoffrey E. Hinton
Video in druga učna gradiva
Oznake: computer science;machine learning
Leto: 2009 Vir: videolectures.net
Št. zadetkov: 30
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