1 Search Results for "Mahsereci, Maren"

Document

Probabilistic Numerical Methods - From Theory to Implementation (Dagstuhl Seminar 21432)

Authors: Philipp Hennig, Ilse C.F. Ipsen, Maren Mahsereci, and Tim Sullivan

Published in: Dagstuhl Reports, Volume 11, Issue 9 (2022)

Abstract

Numerical methods provide the computational foundation of science, and power automated data analysis and inference in its contemporary form of machine learning. Probabilistic numerical methods aim to explicitly represent uncertainty resulting from limited computational resources and imprecise inputs in these models. With theoretical analysis well underway, software development is now a key next step to wide-spread success. This seminar brought together experts from the forefront of machine learning, statistics and numerical analysis to identify important open problems in the field and to lay the theoretical and practical foundation for a software stack for probabilistic numerical methods.

Cite as

Philipp Hennig, Ilse C.F. Ipsen, Maren Mahsereci, and Tim Sullivan. Probabilistic Numerical Methods - From Theory to Implementation (Dagstuhl Seminar 21432). In Dagstuhl Reports, Volume 11, Issue 9, pp. 102-119, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

Copy BibTex To Clipboard

@Article{hennig_et_al:DagRep.11.9.102,
  author =	{Hennig, Philipp and Ipsen, Ilse C.F. and Mahsereci, Maren and Sullivan, Tim},
  title =	{{Probabilistic Numerical Methods - From Theory to Implementation (Dagstuhl Seminar 21432)}},
  pages =	{102--119},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2022},
  volume =	{11},
  number =	{9},
  editor =	{Hennig, Philipp and Ipsen, Ilse C.F. and Mahsereci, Maren and Sullivan, Tim},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.11.9.102},
  URN =		{urn:nbn:de:0030-drops-159208},
  doi =		{10.4230/DagRep.11.9.102},
  annote =	{Keywords: Machine learning, Numerical analysis, Probabilistic numerics}
}

Refine by Author
1 Hennig, Philipp
1 Ipsen, Ilse C.F.
1 Mahsereci, Maren
1 Sullivan, Tim

Refine by Classification
1 Computing methodologies → Machine learning
1 Mathematics of computing → Numerical analysis

Refine by Keyword
1 Machine learning
1 Numerical analysis
1 Probabilistic numerics

Refine by Type
1 document

Refine by Publication Year
1 2022

1 Search Results for "Mahsereci, Maren"

Probabilistic Numerical Methods - From Theory to Implementation (Dagstuhl Seminar 21432)

Abstract

Cite as

Thanks for your feedback!

Could not send message