3 papers
math.DS2026
Data Assimilation for Chemical Reaction Networks and Population Models via a Tunable Observer
Animikh Biswas, Gargi Chaudhuri, Muruhan Rathinam
We consider the problem of state reconstruction for a nonlinear dynamical system from observations of a linear function of the state. We present a design method for a tunable obser…
q-bio.MN2020
State and parameter estimation from exact partial state observation in stochastic reaction networks
Muruhan Rathinam, Mingkai Yu
We consider chemical reaction networks modeled by a discrete state and continuous in time Markov process for the vector copy number of the species and provide a novel particle filt…
math.PR2018
On the Validity of the Girsanov Transformation Method for Sensitivity Analysis of Stochastic Chemical Reaction Networks
Ting Wang, Muruhan Rathinam
We investigate the validity of the Girsanov Transformation (GT) method for parametric sensitivity analysis of stochastic models of chemical reaction networks. The validity depends…