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Scalable Inference for Bayesian Multinomial Logistic-Normal Dynamic Linear Models
Manan Saxena
, Tinghua Chen
,
Justin D. Silverman
College of Information Sciences and Technology
Department of Medicine
Huck Institutes of the Life Sciences
Institute for Computational and Data Sciences (ICDS)
One Health Microbiome Center
Research output
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peer-review
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Keyphrases
Lognormal
100%
Scalable Inference
100%
Three-order
33%
Equivalent Method
33%
Order of Magnitude
33%
Flexible Approach
33%
Novel Algorithm
33%
State Estimation
33%
Computational Challenges
33%
Relative Frequency
33%
Sampling Scheme
33%
Compositional Data
33%
Software Library
33%
User-friendly Software
33%
Total Count
33%
Approximation Accuracy
33%
Joint Inference
33%
Multiple Authors
33%
Multivariate Count Data
33%
C ++
33%
Model Hyperparameters
33%
MAP Estimation
33%
Computer Science
Approximation (Algorithm)
100%
State Estimation
100%
Scientific Field
100%
Sampling Scheme
100%
Software Library
100%
Relative Frequency
100%
Leaning Parameter
100%
Mathematics
Bayesian
100%
Linear Models
100%
Sampling Scheme
33%
Relative Frequency
33%
Marginal Posterior
33%
Total Count
33%