The paper proposes a self-supervised physics-balance loss plus a message-passing optimizer to estimate reaction fluxes from static features, without any supervision from observed flux values.
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Physics Informed Constrained Learning of Dynamics from Static Data
The paper proposes a self-supervised physics-balance loss plus a message-passing optimizer to estimate reaction fluxes from static features, without any supervision from observed flux values.