Mikael Kuusela

According to our database, Mikael Kuusela authored at least 9 papers between 2009 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Downscaling land surface temperature data using edge detection and block-diagonal Gaussian process regression.

Sanjit Dandapanthula, Margaret Johnson, Madeleine Pascolini-Campbell, Glynn C. Hulley, Mikael Kuusela

CoRR, February, 2026

2024

Toward Model-Agnostic Detection of New Physics Using Data-Driven Signal Regions.

Soheun Yi, John Alison, Mikael Kuusela

CoRR, 2024

2023

Quantification of Aquarius, SMAP, SMOS and Argo-Based Gridded Sea Surface Salinity Product Sampling Errors.

Severine Fournier, Frederick M. Bingham, Cristina González-Haro, Akiko Hayashi, Karly M. Ulfsax Carlin, Susannah K. Brodnitz, Verónica González-Gambau, Mikael Kuusela

Remote. Sens., January, 2023

Simulator-Based Inference with WALDO: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problems.

Luca Masserano, Tommaso Dorigo, Rafael Izbicki, Mikael Kuusela, Ann B. Lee

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Objective Frequentist Uncertainty Quantification for Atmospheric \(\mathrm{CO}_2\) Retrievals.

Pratik Patil, Mikael Kuusela, Jonathan Hobbs

SIAM/ASA J. Uncertain. Quantification, 2022

Simulation-Based Inference with WALDO: Perfectly Calibrated Confidence Regions Using Any Prediction or Posterior Estimation Algorithm.

Luca Masserano, Tommaso Dorigo, Rafael Izbicki, Mikael Kuusela, Ann B. Lee

CoRR, 2022

2012

Semi-supervised detection of collective anomalies with an application in high energy particle physics.

Tommi Vatanen, Mikael Kuusela, Eric Malmi, Tapani Raiko, Timo Aaltonen, Yoshikazu Nagai

Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

2010

Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes.

Antti Honkela, Tapani Raiko, Mikael Kuusela, Matti Tornio, Juha Karhunen

J. Mach. Learn. Res., 2010

2009

A gradient-based algorithm competitive with variational Bayesian EM for mixture of Gaussians.

Mikael Kuusela, Tapani Raiko, Antti Honkela, Juha Karhunen

Proceedings of the International Joint Conference on Neural Networks, 2009