Harald Oberhauser
Harald Oberhauser
Mathematical Institute, University of Oxford
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Cited by
Cited by
Kernels for sequentially ordered data
FJ Király, H Oberhauser
Journal of Machine Learning Research 20, 2019
A (rough) pathwise approach to a class of non-linear stochastic partial differential equations
M Caruana, PK Friz, H Oberhauser
Annales de l'Institut Henri Poincaré C, Analyse non linéaire 28 (1), 27-46, 2011
Signature Moments to Characterize Laws of Stochastic Processes
I Chevyrev, H Oberhauser
Journal of Machine Learning Research 23 (176), 1-42, 2022
Persistence paths and signature features in topological data analysis
I Chevyrev, V Nanda, H Oberhauser
IEEE transactions on pattern analysis and machine intelligence 42 (1), 192-202, 2018
Robust filtering: correlated noise and multidimensional observation
D Crisan, J Diehl, PK Friz, H Oberhauser
The Annals of Applied Probability 23 (5), 2139-2160, 2013
Rough path limits of the Wong–Zakai type with a modified drift term
P Friz, H Oberhauser
Journal of Functional Analysis 256 (10), 3236-3256, 2009
A feature set for streams and an application to high-frequency financial tick data
T Lyons, H Ni, H Oberhauser
Proceedings of the 2014 International Conference on Big Data Science and …, 2014
Bayesian learning from sequential data using gaussian processes with signature covariances
C Toth, H Oberhauser
International Conference on Machine Learning, 9548-9560, 2020
Rough path stability of (semi-) linear SPDEs
P Friz, H Oberhauser
Probability Theory and Related Fields 158 (1), 401-434, 2014
A generalized Fernique theorem and applications
P Friz, H Oberhauser
Proceedings of the American Mathematical Society 138 (10), 3679-3688, 2010
A Lévy area between Brownian motion and rough paths with applications to robust nonlinear filtering and rough partial differential equations
J Diehl, H Oberhauser, S Riedel
Stochastic processes and their applications 125 (1), 161-181, 2015
An optimal polynomial approximation of Brownian motion
J Foster, T Lyons, H Oberhauser
SIAM Journal on Numerical Analysis 58 (3), 1393-1421, 2020
Root’s barrier, viscosity solutions of obstacle problems and reflected FBSDEs
P Gassiat, H Oberhauser, G Dos Reis
Stochastic Processes and their Applications 125 (12), 4601-4631, 2015
On the splitting-up method for rough (partial) differential equations
P Friz, H Oberhauser
Journal of Differential Equations 251 (2), 316-338, 2011
The functional Itō formula under the family of continuous semimartingale measures
H Oberhauser
Stochastics and Dynamics 16 (04), 1650010, 2016
Probabilistic supervised learning
F Gressmann, FJ Király, B Mateen, H Oberhauser
arXiv preprint arXiv:1801.00753, 2018
Regularity theory for rough partial differential equations and parabolic comparison revisited
J Diehl, PK Friz, H Oberhauser
Stochastic Analysis and Applications 2014, 203-238, 2014
Adapted topologies and higher rank signatures
P Bonnier, C Liu, H Oberhauser
The Annals of Applied Probability 33 (3), 2136-2175, 2023
The shifted ODE method for underdamped Langevin MCMC
J Foster, T Lyons, H Oberhauser
arXiv preprint arXiv:2101.03446, 2021
An integral equation for Root's barrier and the generation of Brownian increments
P Gassiat, A Mijatović, H Oberhauser
The Annals of Applied Probability, 2039-2065, 2015
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