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Found 8 papers, 4 papers with code
A High Order Solver for Signature Kernels
As bounded variation paths (and more generally geometric $p$-rough paths) can be approximated by piecewise smooth rough paths, one can replace the PDE with rapidly varying coefficients in the original Goursat problem by an explicit system of coupled equations with piecewise constant coefficients derived from the first few iterated integrals of the original input paths.
Novelty Detection on Radio Astronomy Data using Signatures
We demonstrate how SigNova improves the detection of various types of RFI (e. g., broadband and narrowband) in time-frequency visibility data.
Non-adversarial training of Neural SDEs with signature kernel scores
Neural SDEs are continuous-time generative models for sequential data.
Neural signature kernels as infinite-width-depth-limits of controlled ResNets
Motivated by the paradigm of reservoir computing, we consider randomly initialized controlled ResNets defined as Euler-discretizations of neural controlled differential equations (Neural CDEs), a unified architecture which enconpasses both RNNs and ResNets.
Neural Stochastic PDEs: Resolution-Invariant Learning of Continuous Spatiotemporal Dynamics
On the other hand, it extends Neural Operators -- generalizations of neural networks to model mappings between spaces of functions -- in that it can parameterize solution operators of SPDEs depending simultaneously on the initial condition and a realization of the driving noise.
Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes
Stochastic processes are random variables with values in some space of paths.
SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data
Making predictions and quantifying their uncertainty when the input data is sequential is a fundamental learning challenge, recently attracting increasing attention.
Distribution Regression for Sequential Data
In this paper, we develop a rigorous mathematical framework for distribution regression where inputs are complex data streams.
