Robust inference for generalized linear models : binary and poisson regression

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Robust inference for generalized linear models : binary and poisson regression

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Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

Spectral Estimators for High-Dimensional Matrix Inference

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

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Unbiased Likelihood Estimation of Wright–Fisher Diffusion Processes

Reliable data-driven decision-making through optimal transport

Anisotropic Adaptive Finite Elements for a p-Laplacian Problem

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Nonparametric estimation for SDE with sparsely sampled paths: An FDA perspective

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

A Method of Moments Estimator for Interacting Particle Systems and their Mean Field Limit

Random matrix methods for high-dimensional machine learning models

On distributional autoregression and iterated transportation

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Functional data analysis with rough sample paths?

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Iterative removal of sources to model the turbulent electromotive force

Measurement of the Higgs boson production via vector boson fusion and its decay into bottom quarks in proton-proton collisions at √s=13 TeV

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