An efficient Wasserstein-distance approach for reconstructing jump-diffusion processes using parameterized neural networks
We analyze the Wasserstein distance ($ W $-distance) between two probability distributions
associated with two multidimensional jump-diffusion processes. Specifically, we analyze a …
associated with two multidimensional jump-diffusion processes. Specifically, we analyze a …
A local squared Wasserstein-2 method for efficient reconstruction of models with uncertainty
In this paper, we propose a local squared Wasserstein-2 (W_2) method to solve the inverse
problem of reconstructing models with uncertain latent variables or parameters. A key …
problem of reconstructing models with uncertain latent variables or parameters. A key …