461 citations · 461 across the 6 of their papers we have counts for
6 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…
Antithetic Integral Feedback ensures robust perfect adaptation in noisy biomolecular networks
Corentin Briat, Ankit Gupta, Mustafa Khammash
Homeostasis is a running theme in biology. Often achieved through feedback regulation strategies, homeostasis allows living cells to control their internal environment as a means f…