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Journal Articles
- 2023
[j3]Severine Fournier
, Frederick M. Bingham, Cristina González-Haro, Akiko Hayashi, Karly M. Ulfsax Carlin, Susannah K. Brodnitz, Verónica González-Gambau, Mikael Kuusela:
Quantification of Aquarius, SMAP, SMOS and Argo-Based Gridded Sea Surface Salinity Product Sampling Errors. Remote. Sens. 15(2): 422 (2023)- 2022
- [j2]Pratik Patil, Mikael Kuusela, Jonathan Hobbs:
Objective Frequentist Uncertainty Quantification for Atmospheric \(\mathrm{CO}_2\) Retrievals. SIAM/ASA J. Uncertain. Quantification 10(3): 827-859 (2022) - 2010
- [j1]Antti Honkela, Tapani Raiko, Mikael Kuusela, Matti Tornio, Juha Karhunen:
Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes. J. Mach. Learn. Res. 11: 3235-3268 (2010)
Conference and Workshop Papers
- 2023
- [c3]Luca Masserano, Tommaso Dorigo, Rafael Izbicki, Mikael Kuusela, Ann B. Lee:
Simulator-Based Inference with WALDO: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problems. AISTATS 2023: 2960-2974 - 2012
- [c2]Tommi Vatanen, Mikael Kuusela, Eric Malmi, Tapani Raiko, Timo Aaltonen, Yoshikazu Nagai:
Semi-supervised detection of collective anomalies with an application in high energy particle physics. IJCNN 2012: 1-8 - 2009
- [c1]Mikael Kuusela, Tapani Raiko, Antti Honkela, Juha Karhunen:
A gradient-based algorithm competitive with variational Bayesian EM for mixture of Gaussians. IJCNN 2009: 1688-1695
Informal and Other Publications
- 2024
- [i2]Soheun Yi, John Alison, Mikael Kuusela:
Toward Model-Agnostic Detection of New Physics Using Data-Driven Signal Regions. CoRR abs/2409.06960 (2024) - 2022
- [i1]Luca Masserano, Tommaso Dorigo, Rafael Izbicki, Mikael Kuusela, Ann B. Lee:
Simulation-Based Inference with WALDO: Perfectly Calibrated Confidence Regions Using Any Prediction or Posterior Estimation Algorithm. CoRR abs/2205.15680 (2022)
Coauthor Index
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