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1Language Models for Procedural Content Generation
M. Awiszus, A. Dockhorn, A. Hoover, A. Liapis, S. Lucas, M. Eladhari, J. Schrum, and V. Volz. Human-Game AI Interaction (Dagstuhl Seminar 22251), 12 (6): 34-37 (January 2023)
a year ago by @tntl3s
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myown
leibnizailab
Models
Language
myownleibnizailabModelsLanguage
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1Interpreting parameters in the logistic regression model with random effects.
K. Larsen, J. Petersen, E. Budtz-Jørgensen, and L. Endahl. Biometrics, 56 (3): 909-14 (September 2000)3544<m:linebreak></m:linebreak>Regressió logística.
2 years ago by @jepcastel
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Urodela
Male
Biological
SexualBehavior
RandomAllocation
Animal
Animals
Reproduction
OddsRatio
Statistical
Models
RegressionAnalysis
Female
UrodelaMaleBiologicalSexualBehaviorRandomAllocationAnimalAnimalsReproductionOddsRatioStatisticalModelsRegressionAnalysisFemale
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1Time-series analysis of the risk factors for haemorrhagic fever with renal syndrome: comparison of statistical models.
W. Hu, K. Mengersen, P. Bi, and S. Tong. Epidemiology and infection, 135 (2): 245-52 (February 2007)4940<m:linebreak></m:linebreak>JID: 8703737; 2006/04/03 accepted; 2006/06/19 aheadofprint; ppublish;<m:linebreak></m:linebreak>Sèries temporals.
2 years ago by @jepcastel
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Mice:virology
Seasons
Humans
Incidence
DiseaseReservoirs
TimeFactors
Animals
RiskFactors
HemorrhagicFeverwithRenalSyndrome:transmissio
China:epidemiology
EndemicDiseases
China
Statistical
Mice
Models
RuralPopulation
HemorrhagicFeverwithRenalSyndrome:epidemiolog
HemorrhagicFeverwithRenalSyndrome
Mice:virologySeasonsHumansIncidenceDiseaseReservoirsTimeFactorsAnimalsRiskFactorsHemorrhagicFeverwithRenalSyndrome:transmissioChina:epidemiologyEndemicDiseasesChinaStatisticalMiceModelsRuralPopulationHemorrhagicFeverwithRenalSyndrome:epidemiologHemorrhagicFeverwithRenalSyndrome
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1Formal approaches to safety monitoring of clinical trials in life-threatening conditions.
K. Bolland, and J. Whitehead. Statistics in medicine, 19 (21): 2899-917 (November 2000)3639<m:linebreak></m:linebreak>Mesures d'associació.
2 years ago by @jepcastel
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CraniocerebralTrauma
ClinicalTrials
Humans
MyocardialInfarction:mortality
Probability
MyocardialInfarction
ClinicalTrialsasTopic:statistics&numericald
Stroke:mortality
DataInterpretation
Stroke
CraniocerebralTrauma:drugtherapy
MyocardialInfarction:drugtherapy
NormalDistribution
Safety:statistics&numericaldata
CraniocerebralTrauma:mortality
Safety
Statistical
Models
MulticenterStudiesasTopic:statistics&numeric
MulticenterStudiesasTopic
ClinicalTrialsasTopic
Stroke:drugtherapy
PhaseIIIasTopic:statistics&numericaldata
PhaseIIIasTopic
CraniocerebralTraumaClinicalTrialsHumansMyocardialInfarction:mortalityProbabilityMyocardialInfarctionClinicalTrialsasTopic:statistics&numericaldStroke:mortalityDataInterpretationStrokeCraniocerebralTrauma:drugtherapyMyocardialInfarction:drugtherapyNormalDistributionSafety:statistics&numericaldataCraniocerebralTrauma:mortalitySafetyStatisticalModelsMulticenterStudiesasTopic:statistics&numericMulticenterStudiesasTopicClinicalTrialsasTopicStroke:drugtherapyPhaseIIIasTopic:statistics&numericaldataPhaseIIIasTopic
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2Survival analysis in observational studies.
K. Bull, and D. Spiegelhalter. Statistics in medicine, 16 (9): 1041-74 (May 1997)2873<m:linebreak></m:linebreak>Anàlisi de supervivència.
2 years ago by @jepcastel
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OutcomeandProcessAssessment(HealthCare):stat
OutcomeandProcessAssessment(HealthCare)
Humans
SurvivalAnalysis
StatisticsasTopic:methods
LogisticModels
ProportionalHazardsModels
SelectionBias
RandomAllocation
MathematicalComputing
TimeFactors
Algorithms
Statistical
Models
StatisticsasTopic
PulmonaryAtresia
OutcomeandProcessAssessment(HealthCare):statOutcomeandProcessAssessment(HealthCare)HumansSurvivalAnalysisStatisticsasTopic:methodsLogisticModelsProportionalHazardsModelsSelectionBiasRandomAllocationMathematicalComputingTimeFactorsAlgorithmsStatisticalModelsStatisticsasTopicPulmonaryAtresia
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1The two by two diagram: a graphical truth table.
K. Johnson. Journal of clinical epidemiology, 52 (11): 1073-82 (November 1999)3373<m:linebreak></m:linebreak>Proves diagnòstiques.
2 years ago by @jepcastel
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DataDisplay
Research:statistics&numericaldata
EpidemiologicMethods
Humans
Statistical
Models
Research
SensitivityandSpecificity
DataDisplayResearch:statistics&numericaldataEpidemiologicMethodsHumansStatisticalModelsResearchSensitivityandSpecificity
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3Sources of interannual yield variability in JULES-crop and implications for forcing with seasonal weather forecasts
K. Williams, and P. Falloon. Geoscientific Model Development, 8 (12): 3987-3997 (2015)
3 years ago by @lirongyou
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crop
models
cropmodels
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1Climate impacts on global agriculture emerge earlier in new generation of climate and crop models
J. Jägermeyr, C. Müller, A. Ruane, J. Elliott, J. Balkovic, O. Castillo, B. Faye, I. Foster, C. Folberth, J. Franke and 28 other author(s). Nature Food, 2 (11): 873--885 (November 2021)
3 years ago by @lirongyou
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crop
models
climate
cropmodelsclimate
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1Applicability of an Automated Model and Parameter Selection in the Prediction of Screening-Level PTSD in Danish Soldiers Following Deployment: Development Study of Transferable Predictive Models Using Automated Machine Learning
K. "Karstoft, I. "Tsamardinos, K. "Eskelund, Ändersen.SB", and L. "Nissen. JMIR Medical Informatics, (July 2020)
4 years ago by @mensxmachina
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models
Learning
study
selection
parameter
transferable
predictive
Automated
application
AutoML
Machine
modelsLearningstudyselectionparametertransferablepredictiveAutomatedapplicationAutoMLMachine
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1Comparative Study on Effective Turbulence Model for NACA0012 Airfoil using Spalart – Allmaras as a Benchmark
R. Vignesh. International Journal of Trend in Scientific Research and Development, 4 (3): 1049-1056 (March 2020)
4 years ago by @ijtsrd
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CFD
Coefficient
Turbulence
â€“
Spalart
Allmaras
Models
Time
Airfoil
NACA0012
CFDCoefficientTurbulenceâ€“SpalartAllmarasModelsTimeAirfoilNACA0012
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1Granger causality for state space models
L. Barnett, and A. Seth. (2015)cite arxiv:1501.06502Comment: 13 pages, 4 figures.
6 years ago by @tomscag
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models
state-space
modelsstate-space
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1Towards a rigorous assessment of systems biology models: the DREAM3 challenges.
R. Prill, D. Marbach, J. Saez-Rodriguez, P. Sorger, L. Alexopoulos, X. Xue, N. Clarke, G. Altan-Bonnet, and G. Stolovitzky. PloS one, 5 (2): e9202+ (Feb 23, 2010)
6 years ago by @karthikraman
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models
systems-biology
modelssystems-biology
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1A model of the cell-autonomous mammalian circadian clock
H. Mirsky, A. Liu, D. Welsh, S. Kay, and F. Doyle. Proceedings of the National Academy of Sciences, 106 (27): 11107--11112 (Jun 19, 2009)
6 years ago by @karthikraman
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mammalian
models
circadian-clock
mammalianmodelscircadian-clock
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1Population density estimated from locations of individuals on a passive detector array
M. Efford, D. Dawson, and D. Borchers. Ecology, 90 (10): 2676--2682 (September 2009)
8 years ago by @yourwelcome
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based
area
search,
models
density,
spatially
explicit
Likelihood
model,
\_tablet\_modified,
acoustics,
capture-recapture,
basedareasearch,modelsdensity,spatiallyexplicitLikelihoodmodel,\_tablet\_modified,acoustics,capture-recapture,
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1A theory for the combined analysis of ring recovery and recapture data
K. Burnham. Marked Individuals in the Study of Bird Populations, Birkhäuser Verlag, Basel, (1993)
8 years ago by @yourwelcome
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models
open-population
modelsopen-population
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1nIFTy Cosmology: Comparison of Galaxy Formation Models
A. Knebe, F. Pearce, P. Thomas, A. Benson, J. Blaizot, R. Bower, J. Carretero, F. Castander, A. Cattaneo, S. Cora and 26 other author(s). (2015)cite arxiv:1505.04607Comment: 35 pages, 20 figures, accepted for publication in MNRAS.
10 years ago by @miki
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models
galaxy
formation
modelsgalaxyformation
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2The ADAPT Tool: From AADL Architectural Models to Stochastic Petri Nets through Model Transformation
A. Rugina, K. Kanoun, and M. Kaaniche. Dependable Computing Conference, 2008. EDCC 2008. Seventh European, page 85-90. (May 2008)
10 years ago by @avail_map_stud
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models
models
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3Discrete availability models to rejuvenate a telecommunication billing application
T. Dohi, K. Iwamoto, H. Okamura, and N. Kaio. High Assurance Systems Engineering, 2002. Proceedings. 7th IEEE International Symposium on, page 159-166. (2002)
10 years ago by @avail_map_stud
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discrete
models
availability
discretemodelsavailability
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1Preclinical models: status of basic research in depression
E. Nestler, E. Gould, H. Manji, M. Buncan, R. Duman, H. Greshenfeld, R. Hen, S. Koester, I. Lederhendler, M. Meaney and 3 other author(s). Biol Psychiatry, 52 (6): 503-528 (September 2002)
12 years ago by @kilianjay
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models
review
learned_helplessness
modelsreviewlearned_helplessness
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1An open field study of antidepressant drugs
C. Dahl, and K. Götestam. Pharmacol Toxicol, 64 (3): 302-307 (March 1989)
12 years ago by @kilianjay
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models
antidepressant
modelsantidepressant
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publications (hide)69
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