Federated probabilistic modelling for heterogeneous programmable IoT systems

Kaski, Samuel (Principal investigator)
Filstroff, Louis (Project Member)
Jälkö, Joonas (Project Member)
Prediger, Lukas (Project Member)
Kulkarni, Tejas (Project Member)
Mallasto, Anton (Project Member)

Department of Computer Science

Acronym	FIT
Status	Finished
Effective start/end date	04/09/2019 → 31/12/2022

Collaborative partners

Aalto University (lead)
Suomen Akatemia (Project partner)

4 Conference contribution
3 Article
1 Chapter
1 Conference article

Noise-Aware Statistical Inference with Differentially Private Synthetic Data
Räisä, O., Jälkö, J., Kaski, S. & Honkela, A., 2023, Proceedings of The 26th International Conference on Artificial Intelligence and Statistics (AISTATS) 2023. Ruiz, F., Dy, J. & van de Meent, J-W. (eds.). JMLR, p. 3620-3643 (Proceedings of Machine Learning Research; vol. 206).
Research output: Chapter in Book/Report/Conference proceeding › Chapter › Scientific › peer-review

Open Access
File
8 Downloads (Pure)
d3p - A Python Package for Differentially-Private Probabilistic Programming
Prediger, L., Loppi, N., Kaski, S. & Honkela, A., 1 Apr 2022, In: Proceedings of Privacy Enhancing Technologies. 2022, 2, p. 407–425
Research output: Contribution to journal › Conference article › Scientific › peer-review

Open Access
File
45 Downloads (Pure)
Likelihood-Free Inference with Deep Gaussian Processes
Aushev, A., Pesonen, H., Heinonen, M., Corander, J. & Kaski, S., Oct 2022, In: Computational Statistics & Data Analysis. 174, p. 1-19 19 p., 107529.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
File
26 Downloads (Pure)