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Found 5 papers, 1 papers with code
Active and sparse methods in smoothed model checking
In this work we consider extensions to smoothed model checking based on sparse variational methods and active learning.
Experiential AI
Experiential AI is proposed as a new research agenda in which artists and scientists come together to dispel the mystery of algorithms and make their mechanisms vividly apparent.
Geometric fluid approximation for general continuous-time Markov chains
We construct here a general method based on spectral analysis of the transition matrix of the CTMC, without the need for a population structure.
Property-driven State-Space Coarsening for Continuous Time Markov Chains
Dynamical systems with large state-spaces are often expensive to thoroughly explore experimentally.
Unbiased Bayesian Inference for Population Markov Jump Processes via Random Truncations
We consider continuous time Markovian processes where populations of individual agents interact stochastically according to kinetic rules.
