A Recent Development of Particle Methods

Inquiry towards a Continuous Time Limit and Scalability

News
Author

Hirofumi Shiba

Published

2/25/2024

News
The Machine Learning Summer School 2024 (despite its name, it was held in spring due to typhoon considerations) offered me my first opportunity to present in an academic setting.

Tap to Learn More: A Recent Development of Particle Filter

Tap to Learn More: A Recent Development of Particle Filter

Abstract: Recently developments in continuous-time MCMC algorithms have emerged as a promising direction for scalable Bayesian computation. This poster explores their SMC counterparts. A new finding about a continuous-time limit of particle filter is discussed.

MLSS2024

Dates Location
Mar. 4-15, 2024 OIST, Okinawa, Japan

Group Photo at MLSS2024

Group Photo at MLSS2024

Citation

BibTeX citation:
@online{shiba2024,
  author = {Shiba, Hirofumi},
  title = {A {Recent} {Development} of {Particle} {Methods}},
  date = {2024-02-25},
  url = {https://162348.github.io/posts/2024/Poster/RecentDevelopment.html},
  langid = {en},
  abstract = {The Machine Learning Summer School 2024 (despite its name,
    it was held in spring due to typhoon considerations) offered me my
    first opportunity to present in an academic setting.}
}
For attribution, please cite this work as:
Shiba, Hirofumi. 2024. “A Recent Development of Particle Methods.” February 25, 2024. https://162348.github.io/posts/2024/Poster/RecentDevelopment.html.