Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic
Processes

Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes

8 September 2021

Theodoros Damoulas

Papers citing "Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes"

6 / 6 papers shown

Title
High Rank Path Development: an approach of learning the filtration of stochastic processes Jiajie Tao Hao Ni Chong Liu 19 0 0 23 May 2024
Theoretical Foundations of Deep Selective State-Space Models Nicola Muca Cirone Antonio Orvieto Benjamin Walker C. Salvi Terry Lyons Mamba 59 25 0 29 Feb 2024
Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes Georg Manten Cecilia Casolo E. Ferrucci Søren Wengel Mogensen C. Salvi Niki Kilbertus CML BDL 44 8 0 28 Feb 2024
Non-adversarial training of Neural SDEs with signature kernel scores Zacharia Issa Blanka Horvath M. Lemercier C. Salvi AI4TS 40 24 0 25 May 2023
A Fourier representation of kernel Stein discrepancy with application to Goodness-of-Fit tests for measures on infinite dimensional Hilbert spaces George Wynne Mikolaj Kasprzak Andrew B. Duncan 25 4 0 09 Jun 2022
Optimal Stopping via Randomized Neural Networks Calypso Herrera Florian Krack P. Ruyssen Josef Teichmann 46 37 0 28 Apr 2021