Time series filtering, smoothing and learning using the kernel Kalman filter

By Liva Ralaivola, Florence d'Alché-Buc. 2005

63 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Signal Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Stefan Zohren
2. Bryan Lim
3. Stephen J. Roberts
4. W. D. Penny
5. Michael A. Osborne

In Signal Processing

1. Stefan Zohren
2. Bryan Lim
3. Stephen J. Roberts

Citations in the corpus

• Recurrent Neural Filters: Learning Independent Bayesian Filtering Steps for Time Series Prediction (2019, methodology): “This is similar in spirit to the Kernel Kalman Filter [36], allowing for predictions to be made on complex observational datasets – such as raw images – by encoding high dimensional outputs onto a lower dimensional latent representation modelled with a dynamical systems model.”