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Abstract: Flow matching is a recent framework to train generative models that exhibits impressive empirical performance while being relatively easier to train compared with diffusion-based models.

Abstract: This letter proposes a structure-aware automatic differentiation method to accelerate the solution of alternating current optimal power flow (ACOPF) with nonlinear programming (NLP) solvers.

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Note: This book is the first edition of Quantitative Finance with Case Studies in Python. For readers of the second edition, please go to this repo.