Sara Pérez-Vieites
@sperez-vieites.bsky.social
Postdoctoral researcher at Aalto University and FCAI, Helsinki 🇫🇮
Previously in Edinburgh, Lille and Madrid.
Working on Bayesian inference for state-space models, and Bayesian experimental design.
https://sarapv.github.io/
Previously in Edinburgh, Lille and Madrid.
Working on Bayesian inference for state-space models, and Bayesian experimental design.
https://sarapv.github.io/
Call for posters!
We still have room for more contributions and welcome poster submissions to present your work and exchange ideas with our invited speakers and participants.
Poster abstract deadline: this Friday, Sept 12
➡️ easychair.org/cfp/FWC2025
#PosterCall #ControlTheory #AutomaticControl
We still have room for more contributions and welcome poster submissions to present your work and exchange ideas with our invited speakers and participants.
Poster abstract deadline: this Friday, Sept 12
➡️ easychair.org/cfp/FWC2025
#PosterCall #ControlTheory #AutomaticControl
CFP
easychair.org
September 8, 2025 at 12:32 PM
Call for posters!
We still have room for more contributions and welcome poster submissions to present your work and exchange ideas with our invited speakers and participants.
Poster abstract deadline: this Friday, Sept 12
➡️ easychair.org/cfp/FWC2025
#PosterCall #ControlTheory #AutomaticControl
We still have room for more contributions and welcome poster submissions to present your work and exchange ideas with our invited speakers and participants.
Poster abstract deadline: this Friday, Sept 12
➡️ easychair.org/cfp/FWC2025
#PosterCall #ControlTheory #AutomaticControl
🔹 TL;DR: Built on the nested filtering framework, the proposed scheme combines multiple layers of filtering techniques (one for each time scale) to recursively approximate the joint posterior probability distribution of all unknown variables.
📖 Read more [here](doi.org/10.3934/fods...)
📖 Read more [here](doi.org/10.3934/fods...)
Nested smoothing algorithms for inference and tracking of heterogeneous multi-scale state-space systems
Multi-scale problems, where variables of interest evolve in different time-scales and live in different state-spaces, can be found in many fields of science. Here, we introduce a new recursive methodo...
doi.org
February 27, 2025 at 2:01 PM
🔹 TL;DR: Built on the nested filtering framework, the proposed scheme combines multiple layers of filtering techniques (one for each time scale) to recursively approximate the joint posterior probability distribution of all unknown variables.
📖 Read more [here](doi.org/10.3934/fods...)
📖 Read more [here](doi.org/10.3934/fods...)