Sampling low-fidelity outputs for estimation of high-fidelity density and its tails

mjkim1001/mfsampling 28 Feb 2024

This work studies for which low-fidelity outputs, one should obtain high-fidelity outputs, if the goal is to estimate the probability density function of the latter, especially when it comes to the distribution tails and extremes.

Methodology

0
28 Feb 2024

Generalized Bayesian Additive Regression Trees for Restricted Mean Survival Time Inference

mahsaashouri/loss-function-bart-rmst 27 Feb 2024

We propose a generalized Bayes framework that avoids full probability modeling of all survival outcomes by using an RMST-targeted loss function that depends on a collection of inverse probability of censoring weights (IPCW).

Methodology

0
27 Feb 2024

Combined Quantile Forecasting for High-Dimensional Non-Gaussian Data

p-seeun/combined-quantile-forecasting 27 Feb 2024

This study proposes a novel method for forecasting a scalar variable based on high-dimensional predictors that is applicable to various data distributions.

Methodology Applications

0
27 Feb 2024

Algorithm-agnostic significance testing in supervised learning with multimodal data

lucaskook/comets 22 Feb 2024

Valid statistical inference is crucial for decision-making but difficult to obtain in supervised learning with multimodal data, e. g., combinations of clinical features, genomic data, and medical images.

Applications

5
22 Feb 2024

Allowing Growing Dimensional Binary Outcomes via the Multivariate Probit Indian Buffet Process

federicastolf/mvp-ibp 20 Feb 2024

Motivated by ecology applications in which latent features correspond to which species are discovered in a sample, we propose a new class of dependent infinite latent feature models.

Methodology

0
20 Feb 2024

Not all distributional shifts are equal: Fine-grained robust conformal inference

zhimeir/finegrained-conformal-paper 20 Feb 2024

We introduce a fine-grained framework for uncertainty quantification of predictive models under distributional shifts.

Methodology

1
20 Feb 2024

De-Biasing the Bias: Methods for Improving Disparity Assessments with Noisy Group Measurements

swastvedt/weighted-algorithmic-equity 20 Feb 2024

We present novel statistical methods that allow for the use of probabilities of racial/ethnic group membership in assessments of algorithm performance and quantify the statistical bias that results from error in these imputed group probabilities.

Methodology

0
20 Feb 2024

Expressing and visualizing model uncertainty in Bayesian variable selection using Cartesian credible sets

jimegriffin/website 19 Feb 2024

Bayesian variable selection defines a posterior distribution on the possible subsets of the variables (which are usually termed models) to express uncertainty about which variables are strongly linked to the response.

Methodology

0
19 Feb 2024

A frequentist test of proportional colocalization after selecting relevant genetic variants

ash-res/prop-coloc 19 Feb 2024

Colocalization analyses assess whether two traits are affected by the same or distinct causal genetic variants in a single gene region.

Methodology Genomics

2
19 Feb 2024

Non-linear Triple Changes Estimator for Targeted Policies

sinaakbarii/triple-changes 19 Feb 2024

The renowned difference-in-differences (DiD) estimator relies on the assumption of 'parallel trends,' which does not hold in many practical applications.

Methodology Econometrics

0
19 Feb 2024