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ECG ODE-GAN: Learning Ordinary Differential Equations of ECG Dynamics via Generative Adversarial Learning
AAAI Conference on Artificial Intelligence
Understanding the dynamics of complex biological and physiological systems has been explored for many years in the form of physically-based mathematical simulators. The behavior of a physical system is often described via ordinary differential equations (ODE), referred to as the dynamics. In the standard case, the dynamics are derived from purely physical considerations. By contrast, in this work we study how the dynamics can be learned by a generative adversarial network which combines bothdblp:conf/aaai/GolanyFR21 fatcat:boeuuunam5hezkdlkyzhb2u6x4