Maximum likelihood estimation and uncertainty quantification for Gaussian process approximation of deterministic functions T Karvonen, G Wynne, F Tronarp, CJ Oates, S Särkkä SIAM/ASA Journal on Uncertainty Quantification 8 (3), 926–958, 2020 | 42 | 2020 |
A Bayes-Sard cubature method T Karvonen, CJ Oates, S Särkkä Advances in Neural Information Processing Systems 31, 5882–5893, 2018 | 42 | 2018 |
Stability of Linear and Non-Linear Kalman Filters T Karvonen Master's thesis, 2014 | 37 | 2014 |
Maximum likelihood estimation in Gaussian process regression is ill-posed T Karvonen, CJ Oates Journal of Machine Learning Research 24 (120), 1–47, 2023 | 30 | 2023 |
Classical quadrature rules via Gaussian processes T Karvonen, S Särkkä IEEE 27th International Workshop on Machine Learning for Signal Processing …, 2017 | 30 | 2017 |
Fully symmetric kernel quadrature T Karvonen, S Särkkä SIAM Journal on Scientific Computing 40 (2), A697–A720, 2018 | 29 | 2018 |
Student's -filters for noise scale estimation F Tronarp, T Karvonen, S Särkkä IEEE Signal Processing Letters 26 (2), 352–356, 2019 | 21 | 2019 |
Semi-exact control functionals from Sard’s method L South, T Karvonen, C Nemeth, MA Girolami, C Oates Biometrika 109 (2), 351–367, 2022 | 19 | 2022 |
On stability of a class of filters for non-linear stochastic systems T Karvonen, S Bonnabel, E Moulines, S Särkkä SIAM Journal on Control and Optimization 58 (4), 2023–2049, 2020 | 19 | 2020 |
ProbNum: Probabilistic numerics in Python J Wenger, N Krämer, M Pförtner, J Schmidt, N Bosch, N Effenberger, ... arXiv:2112.02100, 2021 | 17* | 2021 |
Student-t process quadratures for filtering of non-linear systems with heavy-tailed noise J Prüher, F Tronarp, T Karvonen, S Särkkä, O Straka 20th International Conference on Information Fusion (FUSION), 2017 | 16 | 2017 |
Asymptotic bounds for smoothness parameter estimates in Gaussian process interpolation T Karvonen SIAM/ASA Journal on Uncertainty Quantification 11 (4), 1225–1257, 2023 | 15* | 2023 |
Symmetry exploits for Bayesian cubature methods T Karvonen, S Särkkä, C Oates Statistics and Computing 29 (6), 1231–1248, 2019 | 15 | 2019 |
Integration in reproducing kernel Hilbert spaces of Gaussian kernels T Karvonen, CJ Oates, M Girolami Mathematics of Computation 90 (331), 2209–2233, 2021 | 14 | 2021 |
On the positivity and magnitudes of Bayesian quadrature weights T Karvonen, M Kanagawa, S Särkkä Statistics and Computing 29 (6), 1317–1333, 2019 | 14 | 2019 |
Gaussian kernel quadrature at scaled Gauss-Hermite nodes T Karvonen, S Särkkä BIT Numerical Mathematics 59 (4), 877–902, 2019 | 14 | 2019 |
Approximate state-space Gaussian processes via spectral transformation T Karvonen, S Särkkä IEEE 26th International Workshop on Machine Learning for Signal Processing …, 2016 | 14 | 2016 |
Taylor moment expansion for continuous-discrete Gaussian filtering Z Zhao, T Karvonen, R Hostettler, S Sarkka IEEE Transactions on Automatic Control 66 (9), 4460–4467, 2021 | 11 | 2021 |
Kernel-based interpolation at approximate Fekete points T Karvonen, S Särkkä, K Tanaka Numerical Algorithms 87 (1), 445–468, 2021 | 11 | 2021 |
Sampling based approximation of linear functionals in reproducing kernel Hilbert spaces G Santin, T Karvonen, B Haasdonk BIT Numerical Mathematics 62, 279–310, 2022 | 10 | 2022 |