D-Index & Metrics Best Publications

Simo Särkkä

Aalto University
Finland

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name Citations Publications World Ranking National Ranking

Computer Science D-index 34 Citations 5,904 211 World Ranking 8034 National Ranking 63

Overview

What is he best known for?

The fields of study Simo Särkkä is best known for:

Statistics
Extended Kalman filter
Differential equation

Simo Särkkä integrates Extended Kalman filter and Invariant extended Kalman filter in his studies. He brings together Invariant extended Kalman filter and Unscented transform to produce work in his papers. In his papers, Simo Särkkä integrates diverse fields, such as Unscented transform and Ensemble Kalman filter. He incorporates Ensemble Kalman filter and Kalman filter in his studies. Simo Särkkä applies his multidisciplinary studies on Kalman filter and Fast Kalman filter in his research. While working in this field, Simo Särkkä studies both Fast Kalman filter and Extended Kalman filter. His Pattern recognition (psychology) research extends to Artificial intelligence, which is thematically connected. Much of his study explores Pattern recognition (psychology) relationship to Artificial intelligence. Simo Särkkä merges Algorithm with Applied mathematics in his research.

His most cited work include:

On Unscented Kalman Filtering for State Estimation of Continuous-Time Nonlinear Systems (450 citations)
Recursive Noise Adaptive Kalman Filtering by Variational Bayesian Approximations (428 citations)
Unscented Rauch--Tung--Striebel Smoother (249 citations)

What are the main themes of his work throughout his whole career to date

His work on Statistics as part of general Parametric statistics research is frequently linked to Telecommunications, thereby connecting diverse disciplines of science. Simo Särkkä integrates several fields in his works, including Statistics and Parametric statistics. Simo Särkkä links relevant scientific disciplines such as Iterated function, Discretization, Taylor series and Hermite polynomials in the realm of Mathematical analysis. His research links Mathematical analysis with Discretization. His research on Quantum mechanics often connects related topics like Gaussian. His Gaussian process research extends to the thematically linked field of Gaussian. As part of his studies on Gaussian process, he frequently links adjacent subjects like Quantum mechanics. His Artificial intelligence study frequently draws connections to other fields, such as Particle filter. Simo Särkkä performs multidisciplinary studies into Particle filter and Kalman filter in his work.

Simo Särkkä most often published in these fields:

Quantum mechanics (76.00%)
Artificial intelligence (72.00%)
Statistics (72.00%)

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.