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Bayesian Parameter Estimation for Stochastic Reaction Networks from Steady-State Observations.

, , and . CMSB, volume 11773 of Lecture Notes in Computer Science, page 342-346. Springer, (2019)

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Approximate inference in latent Gaussian-Markov models from continuous time observations., , and . NIPS, page 971-979. (2013)Robustness of Bayesian Neural Networks to Gradient-Based Attacks., , , , , and . NeurIPS, (2020)Variational inference for Markov jump processes., and . NIPS, page 1105-1112. Curran Associates, Inc., (2007)Variational Estimation in Spatiotemporal Systems From Continuous and Point-Process Observations., , and . IEEE Trans. Signal Process., 60 (7): 3449-3459 (2012)Bayesian Parameter Estimation for Stochastic Reaction Networks from Steady-State Observations., , and . CMSB, volume 11773 of Lecture Notes in Computer Science, page 342-346. Springer, (2019)Experimental Design for Inference over the A. thaliana Circadian Clock Network., , and . CMSB, volume 9308 of Lecture Notes in Computer Science, page 28-39. Springer, (2015)Machine Learning Methods in Statistical Model Checking and System Design - Tutorial., , and . RV, volume 9333 of Lecture Notes in Computer Science, page 323-341. Springer, (2015)Bayesian Statistical parametric Verification and synthesis by Machine Learning., , and . WSC, page 381-394. IEEE, (2018)Studying Emergent Behaviours in Morphogenesis Using Signal Spatio-Temporal Logic., , , , and . HSB, volume 9271 of Lecture Notes in Computer Science, page 156-172. Springer, (2015)A Statistical Approach for Computing Reachability of Non-linear and Stochastic Dynamical Systems., and . QEST, volume 8657 of Lecture Notes in Computer Science, page 41-56. Springer, (2014)