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Large deviations for stochastic evolution equations beyond the coercive case
Using the weak convergence approach, we prove the small-noise large deviation principle (LDP) for stochastic evolution equations in an $L^2$-setting. As the coefficients are allowed to be non-coercive, our framework encompasses a much broader scope than variational settings. In place of coercivity,
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