Deep neural network approximations for high dimensional Kolmogorov PDEs
30 mai 2024 @ 10:45 – 11:45 – Most of the numerical approximation methods for PDEs in the scientific literature suffer from the so-called curse of dimensionality (CoD) in the sense that the number of computational operations and/or the number of parameters employed in the corresponding approximation scheme grows exponentially in the PDE dimension and/or the reciprocal of the desired approximation precision. In […]