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Particle-based Gaussian process optimization for input design in nonlinear dynamical models.

, , , and . CDC, page 2085-2090. IEEE, (2016)

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Detecting and positioning overtaking vehicles using 1D optical flow., , , , and . Intelligent Vehicles Symposium, page 861-866. IEEE, (2014)Particle metropolis hastings using Langevin dynamics., , and . ICASSP, page 6308-6312. IEEE, (2013)Accurate Gaussian Mixture Model Smoothing using a Two-Filter Approach., , , , , and . CDC, page 694-699. IEEE, (2018)Combining Entity Matching Techniques for Detecting Extremist Behavior on Discussion Boards., , , , and . ASONAM, page 850-857. IEEE Computer Society, (2012)Getting started with particle Metropolis-Hastings for inference in nonlinear dynamical models, and . (2015)cite arxiv:1511.01707v4.pdfComment: 36 pages, 8 figures. Submitted to Journal of Statisical Software. Fixed typos and made minior revisions. Source code for R, Python and MATLAB available at: https://github.com/compops/pmh-tutorial.Practical Bayesian System Identification using Hamiltonian Monte Carlo., , , and . CoRR, (2020)A Method for Community Detection in Uncertain Networks., and . EISIC, page 155-162. IEEE Computer Soecity, (2011)Real-Time Robotic Search using Structural Spatial Point Processes., , , , and . UAI, volume 115 of Proceedings of Machine Learning Research, page 995-1005. AUAI Press, (2019)Backward sequential Monte Carlo for marginal smoothing., , and . SSP, page 368-371. IEEE, (2014)Ensemble approaches for improving community detection methods., and . CoRR, (2013)