research
∙
05/25/2023
Non-adversarial training of Neural SDEs with signature kernel scores
Neural SDEs are continuous-time generative models for sequential data. S...
share
research
∙
03/30/2023
Neural signature kernels as infinite-width-depth-limits of controlled ResNets
Motivated by the paradigm of reservoir computing, we consider randomly i...
research
∙
10/19/2021
Neural Stochastic Partial Differential Equations
Stochastic partial differential equations (SPDEs) are the mathematical t...
research
∙
09/08/2021
Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes
Stochastic processes are random variables with values in some space of p...
research
∙
05/10/2021
SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data
Making predictions and quantifying their uncertainty when the input data...
research
∙
02/16/2021