- Referenced in 442 articles
- probabilistic models: discrete-time Markov chains, Markov decision processes and continuous-time Markov chains. Analysis...
- Referenced in 47 articles
- pomp: Statistical Inference for Partially Observed Markov Processes. Tools for working with partially observed Markov...
- Referenced in 71 articles
- bounded reachability analysis for continuous-time Markov decision processes (CTMDPs) and CSL model checking...
- Referenced in 53 articles
- fitting general continuous-time Markov and hidden Markov multi-state models to longitudinal data ... variety of observation schemes are supported, including processes observed at arbitrary times (panel data), continuously ... Markov transition rates and the hidden Markov output process can be modelled in terms...
- Referenced in 32 articles
- exact method to simulate the Markov process corresponding to the reaction-diffusion master equation. Availability...
- Referenced in 25 articles
- solution, based on compact MDD-based Markov processes, are both supported...
- Referenced in 24 articles
- Partially Observable Markov Decision Process (POMDP). The ’pomdp-solve’ program solves problems that are formulated ... partially observable Markov decision processes, a.k.a. POMDPs. It uses the basic dynamic programming approach...
- Referenced in 39 articles
- planning algorithms for POMDPS. Partially Observable Markov Decision Processes (POMDPs) provide a rich framework...
- Referenced in 33 articles
- available when the underlying process is a Markov chain. In addition, discrete-event simulation ... stochastic nature of the process, but certain classes of non-Markov models can still...
- Referenced in 19 articles
- equilibria and long-timescale kinetics of biomolecular processes, such as protein-drug binding, from high ... dimension-reduced data, and estimation of a Markov state model or related model ... employ the variational approach for Markov processes (VAMP) to develop a deep learning framework ... molecular coordinates to Markov states, thus combining the whole data processing pipeline in a single...
- Referenced in 14 articles
- possibly non-deterministic) discrete-time Markov processes (dtMP) defined over uncountable (continuous) state spaces ... finite-state Markov chain or Markov decision processes. The abstraction procedure runs in MATLAB...
- Referenced in 389 articles
- Unfortunately, fitting such models involves computationally intensive Markov chain Monte Carlo (MCMC) methods whose efficiency ... encompassing a wide variety of Gaussian spatial process models for univariate as well as multivariate...
- Referenced in 18 articles
- operational semantics based on (finite) Markov decision processes. LiQuor provides the facility to perform...
- Referenced in 29 articles
- BGPhazard: Markov beta and gamma processes for modeling hazard rates. Computes the hazard rate estimate...
- Referenced in 16 articles
- animal movement modelling using hidden Markov models. These include processing of tracking data, fitting hidden ... Markov models to movement data, visualization of data and fitted model, decoding of the state ... process...
- Referenced in 200 articles
- Krylov subspace projection methods (Arnoldi and Lanczos processes), and that is why the toolkit ... critical importance in the area of Markov chains and furthermore, the computed solution is subject...
- Referenced in 7 articles
- Rapture: a tool for verifying Markov decision processes. We present a tool that performs verification ... quantified reachability properties over Markov decision processes (or probabilistic transition system). The originality...
- Referenced in 117 articles
- Evaluation Process Algebra. PEPA tools: The PEPA process algebra is supported by the PEPA Eclipse ... PEPA editor and performance analysers which use Markov chain or ODE methods or simulation. Performance...
- Referenced in 7 articles
- estimation of discretely observed multi-dimensional diffusion processes using guided proposals. Estimation of parameters ... then be dealt with using a Markov-chain Monte-Carlo method known as data-augmentation ... sampling diffusion bridges. These are Markov processes obtained by adding a guiding term...
- Referenced in 11 articles
- search algorithm for solving First-Order Markov Decision Processes (FOMDPs). Our approach combines first-order...