Trending Research
Bayesian Time Varying Coefficient Model with Applications to Marketing Mix Modeling
Both Bayesian and varying coefficient models are very useful tools in practice as they can be used to model parameter heterogeneity in a generalizable way.
Applications Methodology
Temporal Parallelization of Bayesian Smoothers
EEA-sensors/sequential-parallelization-examples
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This paper presents algorithms for temporal parallelization of Bayesian smoothers.
Computation Distributed, Parallel, and Cluster Computing Dynamical Systems
Pigeons.jl: Distributed Sampling From Intractable Distributions
We introduce a software package, Pigeons. jl, that provides a way to leverage distributed computation to obtain samples from complicated probability distributions, such as multimodal posteriors arising in Bayesian inference and high-dimensional distributions in statistical mechanics.
Computation Distributed, Parallel, and Cluster Computing
ruptures: change point detection in Python
ruptures is a Python library for offline change point detection.
Computation Mathematical Software
Tracking multiple spawning targets using Poisson multi-Bernoulli mixtures on sets of tree trajectories
This paper proposes a Poisson multi-Bernoulli mixture (PMBM) filter on the space of sets of tree trajectories for multiple target tracking with spawning targets.
Methodology Systems and Control Systems and Control Applications
Unified treatment of the asymptotics of asymmetric kernel density estimators
We extend balloon and sample-smoothing estimators, two types of variable-bandwidth kernel density estimators, by a shift parameter and derive their asymptotic properties.
Methodology Statistics Theory Statistics Theory
Conformal Prediction Under Covariate Shift
We extend conformal prediction methodology beyond the case of exchangeable data.
Methodology
A Conceptual Introduction to Hamiltonian Monte Carlo
Hamiltonian Monte Carlo has proven a remarkable empirical success, but only recently have we begun to develop a rigorous under- standing of why it performs so well on difficult problems and how it is best applied in practice.
Methodology
collapse: Advanced and Fast Statistical Computing and Data Transformation in R
collapse is a large C/C++-based infrastructure package facilitating complex statistical computing, data transformation, and exploration tasks in R - at outstanding levels of performance and memory efficiency.
Computation
Synthetic Difference in Differences
We present a new estimator for causal effects with panel data that builds on insights behind the widely used difference in differences and synthetic control methods.
Methodology
