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Mikael Kuusela
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Summertime increases in upper-ocean stratification and mixed-layer depth
JB Sallée, V Pellichero, C Akhoudas, E Pauthenet, L Vignes, S Schmidtko, ...
Nature 591 (7851), 592-598, 2021
2062021
Approximate Riemannian conjugate gradient learning for fixed-form variational Bayes
A Honkela, T Raiko, M Kuusela, M Tornio, J Karhunen
The Journal of Machine Learning Research 11, 3235-3268, 2010
1342010
Locally stationary spatio-temporal interpolation of Argo profiling float data
M Kuusela, ML Stein
Proceedings of the Royal Society A 474 (2220), 20180400, 2018
892018
Heat stored in the Earth system 1960–2020: where does the energy go?
K Von Schuckmann, A Minière, F Gues, FJ Cuesta-Valero, G Kirchengast, ...
Earth System Science Data 15 (4), 1675-1709, 2023
822023
Statistical unfolding of elementary particle spectra: Empirical Bayes estimation and bias-corrected uncertainty quantification
M Kuusela, VM Panaretos
The Annals of Applied Statistics 9 (3), 1671–1705, 2015
46*2015
Semi-supervised anomaly detection–towards model-independent searches of new physics
M Kuusela, T Vatanen, E Malmi, T Raiko, T Aaltonen, Y Nagai
Journal of Physics: Conference Series 368 (1), 012032, 2012
462012
Semi-supervised detection of collective anomalies with an application in high energy particle physics
T Vatanen, M Kuusela, E Malmi, T Raiko, T Aaltonen, Y Nagai
The 2012 International Joint Conference on Neural Networks (IJCNN), 1-8, 2012
412012
Model-independent detection of new physics signals using interpretable SemiSupervised classifier tests
P Chakravarti, M Kuusela, J Lei, L Wasserman
The Annals of Applied Statistics 17 (4), 2759-2795, 2023
332023
Heat stored in the Earth system 1960–2020: where does the energy go?, Earth Syst. Sci. Data, 15, 1675–1709
K Von Schuckmann, A Minière, F Gues, FJ Cuesta-Valero, G Kirchengast, ...
222023
A gradient-based algorithm competitive with variational Bayesian EM for mixture of Gaussians
M Kuusela, T Raiko, A Honkela, J Karhunen
2009 International Joint Conference on Neural Networks, 1688-1695, 2009
212009
Statistical issues in unfolding methods for high energy physics
M Kuusela
172012
Shape-constrained uncertainty quantification in unfolding steeply falling elementary particle spectra
M Kuusela, PB Stark
152017
Uncertainty quantification for wide-bin unfolding: one-at-a-time strict bounds and prior-optimized confidence intervals
M Stanley, P Patil, M Kuusela
Journal of Instrumentation 17 (10), P10013, 2022
122022
Uncertainty quantification in unfolding elementary particle spectra at the Large Hadron Collider
MJ Kuusela
EPFL, 2016
112016
Neural likelihood surfaces for spatial processes with computationally intensive or intractable likelihoods
J Walchessen, A Lenzi, M Kuusela
Spatial Statistics 62, 100848, 2024
102024
Objective Frequentist Uncertainty Quantification for Atmospheric Retrievals
P Patil, M Kuusela, J Hobbs
SIAM/ASA Journal on Uncertainty Quantification 10 (3), 827-859, 2022
92022
Multivariate techniques for identifying diffractive interactions at the LHC
M Kuusela, JW Lämsä, E Malmi, P Mehtälä, R Orava
International Journal of Modern Physics A 25 (08), 1615-1647, 2010
82010
Simulator-based inference with WALDO: Confidence regions by leveraging prediction algorithms and posterior estimators for inverse problems
L Masserano, T Dorigo, R Izbicki, M Kuusela, AB Lee
Proceedings of Machine Learning Research 206, 2023
72023
Background modeling for double Higgs boson production: Density ratios and optimal transport
T Manole, P Bryant, J Alison, M Kuusela, L Wasserman
The Annals of Applied Statistics 18 (4), 2950-2978, 2024
62024
Quantification of Aquarius, SMAP, SMOS and Argo-based gridded sea surface salinity product sampling errors
S Fournier, FM Bingham, C González-Haro, A Hayashi, KM Ulfsax Carlin, ...
Remote Sensing 15 (2), 422, 2023
62023
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