ADM-CLE Approach for Detecting Slow Variables in Continuous Time Markov Chains and Dynamic Data
ADM-CLE Approach for Detecting Slow Variables in Continuous Time Markov Chains and Dynamic Data
A method for detecting intrinsic slow variables in stochastic chemical reaction networks is developed and analyzed. It combines anisotropic diffusion maps (ADMs) with approximations based on the chemical Langevin equation (CLE). The resulting approach, called ADM-CLE, has the potential of being more efficient than the ADM method for a large …