11 citations · 20 across the 8 of their papers we have counts for
9 papers
Spatially orthogonal factor models for spatial transcriptomics and remote sensing data
Dan Cunha, Lukas M. Weber, Mark A. Friedl +1
Principal component analyses are often applied to spatial data towards inference on latent modes of spatial variation. These analyses are widespread across domains including spatia…
A Bayesian Covariance Graphical And Latent Position Model For Multivariate Financial Time Series
Daniel Ahelegbey, Luis Carvalho, Eric Kolaczyk
Current understanding holds that financial contagion is driven mainly by the system-wide interconnectedness of institutions. A distinction has been made between systematic and idio…
Bayesian Network Regularized Regression for Modeling Urban Crime Occurrences
Elizabeth Upton, Luis Carvalho
Analyses of occurrences of residential burglary in urban areas have shown that crime rates are not spatially homogeneous: rates vary across the network of city streets, resulting i…
Bayesian inference on dynamic linear models of day-to-day origin-destination flows in transportation networks
Anselmo Ramalho Pitombeira-Neto, Carlos Felipe Grangeiro Loureiro, Luis Eduardo Carvalho
Estimation of origin-destination (OD) demand plays a key role in successful transportation studies. In this paper, we consider the estimation of time-varying day-to-day OD flows gi…
A Bayesian Change Point Model for Detecting Land Cover Changes in MODIS Time Series
Hunter Glanz, Xiaoman Huang, Minhui Zheng +1
As both a central task in Remote Sensing and a common problem in many other situations involving time series data, change point detection boasts a thorough and well-documented hist…
Perturbation Detection Through Modeling of Gene Expression on a Latent Biological Pathway Network: A Bayesian hierarchical approach
Lisa M. Pham, Luis Carvalho, Scott Schaus +1
Cellular response to a perturbation is the result of a dynamic system of biological variables linked in a complex network. A major challenge in drug and disease studies is identify…
Gene-Proximity Models For Genome-Wide Association Studies
Ian Johnston, Timothy Hancock, Hiroshi Mamitsuka +1
Motivated by the important problem of detecting association between genetic markers and binary traits in genome-wide association studies, we present a novel Bayesian model that est…
Bayesian Degree-Corrected Stochastic Blockmodels for Community Detection
Lijun Peng, Luis Carvalho
Community detection in networks has drawn much attention in diverse fields, especially social sciences. Given its significance, there has been a large body of literature with appro…
Bayesian Centroid Estimation for Motif Discovery
Luis E. Carvalho
Biological sequences may contain patterns that are signal important biomolecular functions; a classical example is regulation of gene expression by transcription factors that bind…