461 citations · 745 across the 22 of their papers we have counts for
28 papers
Interpretable Neural Approximation of Stochastic Reaction Dynamics with Guaranteed Reliability
Quentin Badolle, Arthur Theuer, Zhou Fang +2
Stochastic Reaction Networks (SRNs) are a fundamental modeling framework for systems ranging from chemical kinetics and epidemiology to ecological and synthetic biological processe…
A Spectral Koopman Approximation Framework for Stochastic Reaction Networks
Ankit Gupta, Mustafa Khammash
Stochastic reaction networks (SRNs) are a general class of continuous-time Markov jump processes used to model a wide range of systems, including biochemical dynamics in single cel…
Unbiased estimation of second-order parameter sensitivities for stochastic reaction networks
Quentin Badolle, Ankit Gupta, Mustafa Khammash
Stochastic models for chemical reaction networks are increasingly popular in systems and synthetic biology. These models formulate the reaction dynamics as Continuous-Time Markov C…
The generator gradient estimator is an adjoint state method for stochastic differential equations
Quentin Badolle, Ankit Gupta, Mustafa Khammash
Motivated by the increasing popularity of overparameterized Stochastic Differential Equations (SDEs) like Neural SDEs, Wang, Blanchet and Glynn recently introduced the generator gr…
Effective filtering approach for joint parameter-state estimation in SDEs via Rao-Blackwellization and modularization
Zhou Fang, Ankit Gupta, Mustafa Khammash
Stochastic filtering is a vibrant area of research in both control theory and statistics, with broad applications in many scientific fields. Despite its extensive historical develo…
Complete characterization of robust perfect adaptation in biochemical reaction networks
Yuji Hirono, Ankit Gupta, Mustafa Khammash
Perfect adaptation is a phenomenon whereby the output variables of a system can maintain certain values despite external disturbances. Robust perfect adaptation (RPA) refers to an…