Mikael Kuusela

7 catalog papers. Identity-linked publications and additional name matches are distinguished below.

ORCID: 0000-0001-6875-945X

Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, PA

Publications

• Discussion of “Poisson-FOCuS: An Efficient Online Method for Detecting Count Bursts with Application to Gamma Ray Burst Detection” — Journal of the American Statistical Association 2025
• Background modeling for double Higgs boson production: Density ratios and optimal transport — The Annals of Applied Statistics 2024
• Spatiotemporal local interpolation of global ocean heat transport using Argo floats: A debiased latent Gaussian process approach — The Annals of Applied Statistics 2023
• Model-independent detection of new physics signals using interpretable SemiSupervised classifier tests — The Annals of Applied Statistics 2023
• Shape-constrained uncertainty quantification in unfolding steeply falling elementary particle spectra — The Annals of Applied Statistics 2017
• Statistical unfolding of elementary particle spectra: Empirical Bayes estimation and bias-corrected uncertainty quantification — The Annals of Applied Statistics 2015
• Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes — Journal of Machine Learning Research 2010 (name-matched, not ORCID-linked)