TIC-TAC: A Framework for Improved Covariance Estimation in Deep Heteroscedastic Regression

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TIC-TAC: A Framework for Improved Covariance Estimation in Deep Heteroscedastic Regression

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Random matrix methods for high-dimensional machine learning models

Transportation-based functional ANOVA and PCA for covariance operators

The two-point correlation function covariance with fewer mocks

Experimental Validation of a Unified and Linear State Estimation Method for Hybrid AC/DC Microgrids

Validation of semi-analytical, semi-empirical covariance matrices for two-point correlation function for early DESI data

Positive Definite Completions and Continuous Graphical Models

Detecting whether a stochastic process is finitely expressed in a basis

Linear-Covariance Loss for End-to-End Learning of 6D Pose Estimation

Range-separated hybrid functionals for accurate prediction of band gaps of extended systems

Probing the nature of Dark Energy through the study of large scale structures using spectroscopic surveys and their simulations

DESI mock challenge Halo and galaxy catalogues with the bias assignment method

Towards a multiscale point cloud structural similarity metric

Rapid motion estimation and correction using self-encoded FID navigators in 3D radial MRI

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Small-scale dynamo with finite correlation times

Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations

Saliency prediction in 360° architectural scenes: Performance and impact of daylight variations

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Random Surface Covariance Estimation by Shifted Partial Tracing

Covariance Estimation for Random Surfaces beyond Separability