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Found 3 papers, 2 papers with code
Analysis of the Identifying Regulation with Adversarial Surrogates Algorithm
Given a time-series of noisy measured outputs of a dynamical system z[k], k=1... N, the Identifying Regulation with Adversarial Surrogates (IRAS) algorithm aims to find a non-trivial first integral of the system, namely, a scalar function g() such that g(z[i]) = g(z[j]), for all i, j.
Identifying Dynamic Regulation with Adversarial Surrogates
Homeostasis, the ability to maintain a stable internal environment in the face of perturbations, is essential for the functioning of living systems.
Enhancing Causal Estimation through Unlabeled Offline Data
Our proposed approach consists of three stages: (i) Use the abundant offline data in order to create both a non-causal and a causal estimator for the relevant unmeasured physiological variables.
