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
241 2021 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
131 2010 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
108 2023 Locally stationary spatio-temporal interpolation of Argo profiling float data M Kuusela, ML Stein
Proceedings of the Royal Society A 474 (2220), 20180400, 2018
91 2018 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
51 2024 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
48 2012 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
47 * 2015 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
43 2012 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
39 2023 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, ...
29 2023 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
20 2009 Statistical issues in unfolding methods for high energy physics M Kuusela
17 2012 Shape-constrained uncertainty quantification in unfolding steeply falling elementary particle spectra M Kuusela, PB Stark
16 2017 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
arXiv preprint arXiv:2205.15680, 2022
15 2022 Neural likelihood surfaces for spatial processes with computationally intensive or intractable likelihoods J Walchessen, A Lenzi, M Kuusela
Spatial Statistics 62, 100848, 2024
13 2024 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
12 2022 Uncertainty quantification in unfolding elementary particle spectra at the Large Hadron Collider MJ Kuusela
EPFL, 2016
12 2016 Trends and variability in Earth’s energy imbalance and ocean heat uptake since 2005 MZ Hakuba, S Fourest, T Boyer, B Meyssignac, JA Carton, G Forget, ...
Surveys in Geophysics, 1-36, 2024
9 2024 Objective Frequentist Uncertainty Quantification for Atmospheric P Patil, M Kuusela, J Hobbs
SIAM/ASA Journal on Uncertainty Quantification 10 (3), 827-859, 2022
9 2022 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
8 2023