A Scalable Bayesian Sampling Method Based on Stochastic Gradient Descent Isotropization von Franzese, Giulio, Milios, Dimitrios, Filippone, Maurizio, Michiardi, Pietro

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Smoothed model checking for uncertain Continuous-Time Markov Chains von Bortolussi, Luca, Milios, Dimitrios, Sanguinetti, Guido

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Variational Bootstrap for Classification von Kozyrskiy, Bogdan, Milios, Dimitrios, Filippone, Maurizio

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Component aggregation for PEPA models: An approach based on approximate strong equivalence von Milios, Dimitrios, Gilmore, Stephen

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Policy learning in continuous-time Markov decision processes using Gaussian Processes von Bartocci, Ezio, Bortolussi, Luca, Brázdil, Tomáš, Milios, Dimitrios, Sanguinetti, Guido

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Probabilistic Model Checking for Continuous-Time Markov Chains via Sequential Bayesian Inference von Milios, Dimitrios, Sanguinetti, Guido, Schnoerr, David

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On approximating the stochastic behaviour of Markovian process algebra models von Milios, Dimitrios

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U-Check: Model Checking and Parameter Synthesis Under Uncertainty von Bortolussi, Luca, Milios, Dimitrios, Sanguinetti, Guido

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Efficient Stochastic Simulation of Systems with Multiple Time Scales via Statistical Abstraction von Bortolussi, Luca, Milios, Dimitrios, Sanguinetti, Guido

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Compositional Approximate Markov Chain Aggregation for PEPA Models von Milios, Dimitrios, Gilmore, Stephen

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Studying Emergent Behaviours in Morphogenesis Using Signal Spatio-Temporal Logic von Bartocci, Ezio, Bortolussi, Luca, Milios, Dimitrios, Nenzi, Laura, Sanguinetti, Guido

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Machine Learning Methods in Statistical Model Checking and System Design – Tutorial von Bortolussi, Luca, Milios, Dimitrios, Sanguinetti, Guido

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Property-Driven State-Space Coarsening for Continuous Time Markov Chains von Michaelides, Michalis, Milios, Dimitrios, Hillston, Jane, Sanguinetti, Guido

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A Variational View on Bootstrap Ensembles as Bayesian Inference von Milios, Dimitrios, Michiardi, Pietro, Filippone, Maurizio

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Markov Chain Simulation with Fewer Random Samples von Milios, Dimitrios, Gilmore, Stephen

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Probabilistic Programming Process Algebra von Georgoulas, Anastasis, Hillston, Jane, Milios, Dimitrios, Sanguinetti, Guido

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Revisiting the Effects of Stochasticity for Hamiltonian Samplers von Franzese, Giulio, Milios, Dimitrios, Filippone, Maurizio, Michiardi, Pietro

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Policy Learning for Time-Bounded Reachability in Continuous-Time Markov Decision Processes via Doubly-Stochastic Gradient Ascent von Bartocci, Ezio, Bortolussi, Luca, Brázdil, Tomǎš, Milios, Dimitrios, Sanguinetti, Guido

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All You Need is a Good Functional Prior for Bayesian Deep Learning von Tran, Ba-Hien, Rossi, Simone, Milios, Dimitrios, Filippone, Maurizio

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Sparse within Sparse Gaussian Processes using Neighbor Information von Tran, Gia-Lac, Milios, Dimitrios, Michiardi, Pietro, Filippone, Maurizio

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