Activities & Results
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Activities, awards, and other outputs
- Tutorial at the IEEE International Conference on Signal Processing and Communications (SPCOM) 2022. Tutorial title: Generative models and role of deep neural networks. Lecturer: Saikat Chatterjee.
- Two-day Tutorial at Digital Futures on the Fundamentals of Bayesian Inference using Probabilistic Programming Probabilistic programming. Lecturer: David Broman.
- Distinguished Artifact Award at European Symposium on Programming (ESOP 2022), for the paper Compiling Universal Probabilistic Programming Languages with Efficient Parallel Sequential Monte Carlo Inference. David Broman and co-authors.
- Keynote at the Workshop on Nonlinear System Identification Benchmarks. Speaker: Håkan Hjalmarsson
- Organization of the Data-limited learning workshop (DLL) in fall 2021. Organized by David Broman together with Co-PIs.
- Organization of the MATH, AI, and Neuroscience (MAIN) workshop at Digital Futures in 2021. Organizer: Saikat Chatterjee
- Invited talk at the Stochastic Networks conference (Cornell in 2022). Speaker: Alexandre Proutiere
- Keynote at YEQTIV Eindhoven and in the SNAPP seminar series. Speaker: Alexandre Proutiere
- The organizer of the International Conference on Embedded Software (EMSOFT), the premier venue for embedded software, 2022. PC Chair: David Broman
This project has so far resulted in several fundamental research results. The results include but are not limited to: a new biological modelling approach that includes transcriptional information, new system identification techniques for differential-algebraic equations subject to disturbances, fundamental limits for sample complexity and lower bounds for the regret of deterministic discrete dynamical systems.
The results are published in top-tier journals and conferences such as ICML, NeurIPS, and CDC.