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1A network model of correlated growth of tissue stiffening in pulmonary fibrosis
C. Oliveira, J. Bates, and B. Suki. NEW JOURNAL OF PHYSICS, (2014)
3 years ago by @ppgfis_ufc_br
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random
percolation;
{pulmonary
fibrosis;
walk}
model;
network
modulus;
bulk
randompercolation;{pulmonaryfibrosis;walk}model;networkmodulus;bulk
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2Critical behavior of the 3D Ising model on a poissonian random lattice
F. Lima, U. Costa, and R. Filho. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 387 (7): 1545-1550 (2008)
3 years ago by @ppgfis_ufc_br
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random
lattices;
critical
exponents}
{ferromagnetic
model;
Carlo
Ising
Monte
methods;
randomlattices;criticalexponents}{ferromagneticmodel;CarloIsingMontemethods;
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1Potts model on directed small-world Voronoi-Delaunay lattices
R. Marques, F. Lima, and R. Filho. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, (2016)
3 years ago by @ppgfis_ufc_br
show all tags
lattices}
Random
{Potts
Voronoi-Delaunay
model;
systems;
lattices}Random{PottsVoronoi-Delaunaymodel;systems;
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1Complex fluctuations and robustness in stylized signalling networks
A. Diaz-Guilera, A. Moreira, L. Guzman, and L. Amaral. JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT, (2007)
3 years ago by @ppgfis_ufc_br
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random
graphs;
{network
networks}
dynamics;
randomgraphs;{networknetworks}dynamics;
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1Prediction of Cervical Cancer using Machine Learning and Deep Learning Algorithms
K. Kanimozhi. International Journal of Trend in Scientific Research and Development, 4 (6): 426-430 (September 2020)
4 years ago by @ijtsrd
show all tags
Cancer
SVM
Dataset
learning
Decision
Deep
networks
Machine
Logistic
Random
Cervical
regression
Forest
Tree
Neural
CancerSVMDatasetlearningDecisionDeepnetworksMachineLogisticRandomCervicalregressionForestTreeNeural
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6Random walks for text semantic similarity
D. Ramage, A. Rafferty, and C. Manning. Proceedings of the 2009 workshop on graph-based methods for natural language processing, page 23--31. Association for Computational Linguistics, (2009)
7 years ago by @thoni
show all tags
random
semantic
walks
citedby:scholar:count:78
similarity
citedby:scholar:timestamp:2017-12-21
randomsemanticwalkscitedby:scholar:count:78similaritycitedby:scholar:timestamp:2017-12-21
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1Hierarchical Bayes for structured, variable populations: from recapture data to life-history prediction
J. Clark, G. Ferraz, N. Oguge, H. Hays, and J. DiCostanzo. Ecology, 86 (8): 2232--2244 (2005)
8 years ago by @yourwelcome
show all tags
Markov
chain
processes,
Bayesian
birds,
distribution,
monte
model,
multivariate
Monte
inference,
random
effects
Dirichlet-multinomial
Carlo,
prior
carlo
hierarchical
mammals,
chain,
capture-recapture,
markov
Markovchainprocesses,Bayesianbirds,distribution,montemodel,multivariateMonteinference,randomeffectsDirichlet-multinomialCarlo,priorcarlohierarchicalmammals,chain,capture-recapture,markov
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1Adjusting for network size and composition effects in exponential-family random graph models
P. Krivitsky, M. Handcock, and M. Morris. Statistical Methodology, 8 (4): 319--339 (July 2011)
8 years ago by @yourwelcome
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random
exponential
social
model,
density
networks
graph
dependence,
randomexponentialsocialmodel,densitynetworksgraphdependence,
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1An extravariation model for improving confidence intervals of population size estimates from removal data.
Y. Wang, and N. Loneragan. Canadian Journal of Fisheries and Aquatic Sciences, (1996)
8 years ago by @yourwelcome
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random
effects
overdispersion,
model,
mixed
capture-recapture,
randomeffectsoverdispersion,model,mixedcapture-recapture,
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1Stochastic Simulation in Agricultural Economics
A. Jain, A. Pathak, N. Safoora, N. Vaz, and M. Prajakta. International Journal on Recent and Innovation Trends in Computing and Communication, 3 (4): 2162--2167 (April 2015)
9 years ago by @ijritcc
show all tags
economics
futures
Random
market
data
Agricultural
Data
Stochastic
Modelling
analysis
Mining
walk
economicsfuturesRandommarketdataAgriculturalDataStochasticModellinganalysisMiningwalk
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1A Bayesian framework for glaucoma progression detection using Heidelberg Retina Tomograph images
M. Akram Belghith Christopher Bowd. International Journal of Advanced Computer Science and Applications(IJACSA), (2013)
11 years ago by @thesaiorg
show all tags
random
Markov
Bayesian
field,
estimation,
change
detec-tion,Glaucoma
randomMarkovBayesianfield,estimation,changedetec-tion,Glaucoma
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3Image Completion Using Efficient Belief Propagation Via Priority Scheduling and Dynamic Pruning
N. Komodakis, and G. Tziritas. IEEE Trans. on Image Processing, 16 (11): 2649--2661 (2007)
11 years ago by @guillem.palou
show all tags
image
domain-specific
Markov
tasks,
processes
processing,
knowledge,
problem,
texture
label
synthesis,Markov
message
priority-based
completion,
discrete
field,
inpainting,
schedulingbelief
propagation,
object
image-editing
global
texture,
random
vision,
removal,
computer
optimization
pruning,
prior
scheduling,
optimisation,
text
dynamic
imagedomain-specificMarkovtasks,processesprocessing,knowledge,problem,texturelabelsynthesis,Markovmessagepriority-basedcompletion,discretefield,inpainting,schedulingbeliefpropagation,objectimage-editingglobaltexture,randomvision,removal,computeroptimizationpruning,priorscheduling,optimisation,textdynamic
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1Dynamic spectrum access in open spectrum wireless networks
Y. Xing, R. Chandramouli, S. Mangold, and S. N. IEEE Journal on Selected Areas in Communication, 24 (3): 626 - 637 (2006)
12 years ago by @chsivic
show all tags
Markov
bandwidth
protocol;
limitation;
queueing
Commission;
Communications
anthropological
models;
FCC;
spectrum
continuous-time
wireless
model;
theory;
agile
open
Federal
access
network;
analysis;
radio
management;
random
egualis
radio;
reform;
processes;
homo
dynamic
policy
allocation;
protocols;
Markovbandwidthprotocol;limitation;queueingCommission;Communicationsanthropologicalmodels;FCC;spectrumcontinuous-timewirelessmodel;theory;agileopenFederalaccessnetwork;analysis;radiomanagement;randomegualisradio;reform;processes;homodynamicpolicyallocation;protocols;
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31Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
J. Lafferty, A. McCallum, and F. Pereira. Proceedings of the Eighteenth International Conference on Machine Learning, page 282--289. San Francisco, CA, USA, Morgan Kaufmann Publishers Inc., (2001)
12 years ago by @jil
show all tags
random
bias
conditional
field
crf
state
fields
randombiasconditionalfieldcrfstatefields
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1On oblique random forests
B. Menze, B. Kelm, D. Splitthoff, U. Koethe, and F. Hamprecht. Proceedings of the ECML/PKDD 2011, (2011)
13 years ago by @ecml_pkdd_2011
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random
oblique
learning
2011
ensemble
forests
ecml_pkdd_2011
randomobliquelearning2011ensembleforestsecml_pkdd_2011
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1Correlations between structure and random walk dynamics in directed complex networks
L. Costa, O. Sporns, L. Antiqueira, M. Nunes, and O. Oliveira Jr.. Applied Physics Letters, 91 (5): 054107 (2007)
14 years ago by @lantiq
show all tags
random
myown
dynamics
correlations
networks
structure
walk
randommyowndynamicscorrelationsnetworksstructurewalk
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1Using species distribution models to predict new occurrences for rare plants
J. Williams, C. Seo, J. Thorne, J. Nelson, S. Erwin, J. O'Brien, and M. Schwartz. Diversity and Distributions, (2009)
15 years ago by @pillo
show all tags
random
endemism,
specialist,
Maxent,
rarity,
forests,
Edaphic
serpentine
randomendemism,specialist,Maxent,rarity,forests,Edaphicserpentine
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2Approximate nearest neighbors and the fast Johnson-Lindenstrauss transform
N. Ailon, and B. Chazelle. (2006)
15 years ago by @cdevries
show all tags
random
projection
nearestneighbour
randomprojectionnearestneighbour
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1Inadmissibility of an estimator for the ratio of variance components
K. Das, Q. Meneghini, and N. Giri. Statistics & Probability Letters, 10 (2): 151--157 (July 1990)
17 years ago by @smicha
show all tags
effects
Random
model
effectsRandommodel
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1On the efficiency of prediction estimators in two-stage sampling
D. Bellhouse, and J. Rao. Journal of Statistical Planning and Inference, (1986)
17 years ago by @smicha
show all tags
models
Random
permutation
modelsRandompermutation
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publications (hide)32
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