Moritz Schauer

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Frank van der MeulenVrije Universiteit AmsterdamVerified email at vu.nl
Shota GugushviliWageningen University & ResearchVerified email at yesdatasolutions.com
Peter SpreijUniversiteit van Amsterdam, Korteweg-de Vries Institute for MathematicsVerified email at uva.nl
Harry van ZantenVerified email at vu.nl
Joris BierkensTechnische Universiteit DelftVerified email at tudelft.nl
Sebastiano GrazziResearch Associate, Department of Statistics, University of WarwickVerified email at warwick.ac.uk
Frank SchäferMassachusetts Institute of TechnologyVerified email at mit.edu
Christopher Vincent RackauckasMassachusetts Institute of TechnologyVerified email at mit.edu
Gaurav AryaCarnegie Mellon UniversityVerified email at cmu.edu
Stefan SommerProfessor at University of CopenhagenVerified email at di.ku.dk
Prof. Dr. Denis BelomestnyDuisburg-Essen UniversityVerified email at uni-due.de
Alexis ArnaudonEcole Polytechnique Federale de LausanneVerified email at epfl.ch
Jan van WaaijDepartment of Health Technology, Section for Bioinformatics, Danish University of TechnologyVerified email at dtu.dk
Ruben SeyerPhD student in Mathematical Statistics, Chalmers/University of GothenburgVerified email at chalmers.se
Alexander K. LewGraduate student, MITVerified email at mit.edu
Mathieu HuotResearch Scientist, MITVerified email at crans.org
Kartik ChandraMIT (PhD student)Verified email at cs.stanford.edu
Christos PelekisAristotle University of ThessalonikiVerified email at math.auth.gr
Sebastian J. VollmerUniversity of Kaiserslautern/DFKIVerified email at cs.uni-kl.de
Raphael SonabendImperial College LondonVerified email at imperial.ac.uk

Moritz Schauer

Chalmers University of Technology and University of Gothenburg

Verified email at chalmers.se - Homepage

Statistics with math and machines


Title Sort by citations Sort by year Sort by 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	81	2017
Bayesian estimation of discretely observed multi-dimensional diffusion processes using guided proposals F van der Meulen, M Schauer	67	2017
Automatic Differentiation of Programs with Discrete Randomness G Arya, M Schauer, F Schäfer, C Rackauckas Advances in Neural Information Processing Systems, 2022	50	2022
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	46	2014
Continuous-discrete smoothing of diffusions M Mider, M Schauer, F van der Meulen Electronic Journal of Statistics 15 (2), pp. 4295–4342, 2021	38	2021
Associations of mindful eating domains with depressive symptoms and depression in three European countries LHH Winkens, T van Strien, IA Brouwer, BWJH Penninx, M Visser, ... Journal of affective disorders 228, 26-32, 2018	35	2018
Learning the causal structure of copula models with latent variables R Cui, P Groot, M Schauer, T Heskes Corvallis: AUAI Press, 2018	28	2018
Bayesian estimation of incompletely observed diffusions F van der Meulen, M Schauer Stochastics 90 (5), 641-662, 2018	26	2018
A piecewise deterministic Monte Carlo method for diffusion bridges J Bierkens, S Grazzi, F van der Meulen, M Schauer Statistics and Computing 31, 2021	24	2021
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	22	2020
Sticky PDMP samplers for sparse and local inference problems J Bierkens, S Grazzi, F Meulen, M Schauer Statistics and Computing 33 (1), 8, 2023	20	2023
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	20	2019
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	19*	2022
Automatic backward filtering forward guiding for Markov processes and graphical models F Van der Meulen, M Schauer arXiv preprint arXiv:2010.03509, 2020	16	2020
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	12	2018
Differentiating Metropolis-Hastings to Optimize Intractable Densities G Arya, R Seyer, F Schäfer, A Lew, M Huot, VK Mansinghka, ... Differentiable Almost Everything Workshop of ICML 2023; arXiv preprint arXiv …, 2023	9	2023
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	9*	2019
Conditioning continuous-time Markov processes by guiding M Corstanje, F van der Meulen, M Schauer Stochastics 95 (6), 963-996, 2023	7	2023
Network coloring and colored coin games C Pelekis, M Schauer Search Theory: A Game Theoretic Perspective, 59-73, 2013	7	2013
Methods and applications of PDMP samplers with boundary conditions J Bierkens, S Grazzi, G Roberts, M Schauer arXiv preprint arXiv:2303.08023, 2023	6	2023

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