Follow
Moritz Schauer
Title
Cited by
Cited by
Year
Guided proposals for simulating multi-dimensional diffusion bridges
M Schauer, F van der Meulen, H van Zanten
Bernoulli 23 (4A), 2917–2950, 2017
652017
Bayesian estimation of discretely observed multi-dimensional diffusion processes using guided proposals
F van der Meulen, M Schauer
602017
Reversible jump MCMC for nonparametric drift estimation for diffusion processes
F van der Meulen, M Schauer, H van Zanten
Computational Statistics & Data Analysis 71, 615-632, 2014
462014
Continuous-discrete smoothing of diffusions
M Mider, M Schauer, F van der Meulen
Electronic Journal of Statistics 15 (2), pp. 4295–4342, 2021
29*2021
Bayesian estimation of incompletely observed diffusions
F van der Meulen, M Schauer
Stochastics 90 (5), 641-662, 2018
232018
Automatic Differentiation of Programs with Discrete Randomness
G Arya, M Schauer, F Schäfer, C Rackauckas
Advances in Neural Information Processing Systems, 2022
222022
Learning the causal structure of copula models with latent variables
R Cui, P Groot, M Schauer, T Heskes
Corvallis: AUAI Press, 2018
222018
A piecewise deterministic Monte Carlo method for diffusion bridges
J Bierkens, S Grazzi, F van der Meulen, M Schauer
Statistics and Computing 31, 2021
172021
Simulation of elliptic and hypo-elliptic conditional diffusions
J Bierkens, F van der Meulen, M Schauer
Advances in Applied Probability 52 (1), 173-212, 2020
172020
Fast and scalable non-parametric Bayesian inference for Poisson point processes
S Gugushvili, F van der Meulen, M Schauer, P Spreij
RESEARCHERS.ONE, 2019, https://www.researchers.one/article/2019-06-6, with …, 2019
162019
Diffusion bridges for stochastic Hamiltonian systems with applications to shape analysis
A Arnaudon, F van der Meulen, M Schauer, S Sommer
SIAM Journal on Imaging Sciences 15 (1), 293-323, 2022
15*2022
Automatic backward filtering forward guiding for Markov processes and graphical models
F Van der Meulen, M Schauer
arXiv preprint arXiv:2010.03509, 2020
132020
Adaptive nonparametric drift estimation for diffusion processes using Faber-Schauder expansions
F van der Meulen, M Schauer, J van Waaij
Statistical Inference for Stochastic Processes 21 (3), 603-628, 2018
132018
Sticky PDMP samplers for sparse and local inference problems
J Bierkens, S Grazzi, F Meulen, M Schauer
Statistics and Computing 33 (1), 8, 2023
102023
Nonparametric Bayesian inference for Gamma-type Lévy subordinators
D Belomestny, S Gugushvili, M Schauer, P Spreij
Communications in Mathematical Sciences 17 (3), 781-816, 2019
8*2019
Nonparametric Bayesian volatility estimation
S Gugushvili, F der Meulen, M Schauer, P Spreij
2017 MATRIX annals, 279-302, 2019
72019
Network coloring and colored coin games
C Pelekis, M Schauer
Search Theory: A Game Theoretic Perspective, 59-73, 2013
72013
Nonparametric Bayesian estimation of a Hölder continuous diffusion coefficient
S Gugushvili, F van der Meulen, M Schauer, P Spreij
62020
Nonparametric Bayesian volatility learning under microstructure noise
S Gugushvili, F van der Meulen, M Schauer, P Spreij
arXiv preprint arXiv:1805.05606, 2018
6*2018
Flexible group fairness metrics for survival analysis
R Sonabend, F Pfisterer, A Mishler, M Schauer, L Burk, S Mukherjee, ...
DSHealth 2022 (Workshop on Applied Data Science for Healthcare); arXiv …, 2022
52022
The system can't perform the operation now. Try again later.
Articles 1–20