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Watch this 18-minute conference talk from the LAFI 2025 workshop that introduces SSMProblems.jl and GeneralisedFilters.jl, two Julia packages within the Turing.jl ecosystem designed to address challenges in state space model (SSM) programming. Learn how these packages provide a consistent, composable, and general framework for defining SSMs and performing inference across various fields from econometrics to robotics. The presentation demonstrates how the unified interface enables researchers to easily define a wide range of SSMs and apply various inference algorithms including Kalman filtering, particle filtering, and combinations thereof. Discover how these tools promote code reuse and modularity while prioritizing scalability through efficient memory management and GPU-acceleration for handling large-scale inference tasks. Presented by researchers from the University of Cambridge and the Federal Reserve Board of Governors at the ACM SIGPLAN-sponsored LAFI workshop.
