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Meeting ID: 819 1201 3907

Passcode: nbps2024

Regularization by noise in the context of stochastic differential equations (SDEs)  with coefficients of low regularity, known as singular SDEs, refers to the beneficial effect produced by noise so that the singularity from the coefficients is smoothed out yielding well-behaved equations. This field, initiated  by works of Zvonkin and Veretennikov from 70’s, has been extensively explored among different concepts from stochastic calculus. In this talk we will introduce the ideas from classical Itô calculus, involving partial differential equation (PDE) theory and modern tools from rough path theory and Malliavin calculus, to address problems related to the well-posedness and numerics of singular SDEs driven by different types of noise, particularly multiplicative Gaussian noise.