
Optimal Experimental Design for Mathematical Models of Hematopoiesis
The hematopoietic system has a highly regulated and complex structure in...
read it

Conjoined Dirichlet Process
Biclustering is a class of techniques that simultaneously clusters the r...
read it

Bayesian Neural Decoding Using A DiversityEncouraging Latent Representation Learning Method
It is well established that temporal organization is critical to memory,...
read it

Deep Markov Chain Monte Carlo
We propose a new computationally efficient sampling scheme for Bayesian ...
read it

Modeling Dynamic Functional Connectivity with Latent Factor Gaussian Processes
Dynamic functional connectivity, as measured by the timevarying covaria...
read it

A Flexible Joint LongitudinalSurvival Modeling Framework for Incorporating Multiple Longitudinal Biomarkers
We are interested in survival analysis of hemodialysis patients for whom...
read it

A Bayesian Framework for NonCollapsible Models
In this paper, we discuss the noncollapsibility concept and propose a n...
read it

A Flexible Joint LongitudinalSurvival Model for Analysis of EndStage Renal Disease Data
We propose a flexible joint longitudinalsurvival framework to examine t...
read it

Modeling Binary Time Series Using Gaussian Processes with Application to Predicting Sleep States
Motivated by the problem of predicting sleep states, we develop a mixed ...
read it

Neural Network Gradient Hamiltonian Monte Carlo
Hamiltonian Monte Carlo is a widely used algorithm for sampling from pos...
read it

Flexible Bayesian Dynamic Modeling of Correlation and Covariance Matrices
Modeling correlation (and covariance) matrices is a challenging problem ...
read it

Bayesian Inference on Matrix Manifolds for Linear Dimensionality Reduction
We reframe linear dimensionality reduction as a problem of Bayesian infe...
read it

Variational Hamiltonian Monte Carlo via Score Matching
Traditionally, the field of computational Bayesian statistics has been d...
read it

Sampling constrained probability distributions using Spherical Augmentation
Statistical models with constrained probability distributions are abunda...
read it

Hamiltonian Monte Carlo Acceleration Using Surrogate Functions with Random Bases
For big data analysis, high computational cost for Bayesian methods ofte...
read it

Dependent Matérn Processes for Multivariate Time Series
For the challenging task of modeling multivariate time series, we propos...
read it

Split HMC for Gaussian Process Models
In this paper, we discuss an extension of the Split Hamiltonian Monte Ca...
read it
Babak Shahbaba
is this you? claim profile