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ORCIDMichael Tiemann 0001
Person information
- affiliation: University of Tübingen, Germany
- affiliation (former): Bosch Center for Artificial Intelligence, Renningen, Germany
Other persons with the same name
- Michael Tiemann 0002
![[0000-0001-7136-2744]](https://devdomain4test.ir/img/orcid-mark.12x12.png "0000-0001-7136-2744")
— Federal Institute for Vocational Education and Training (BIBB), Bonn, Germany (and 1 more) - Michael Tiemann 0003 — Red Hat, Inc, Raleigh, NC, USA
- Michael Tiemann 0004 — University of Paderborn, Paderborn, Germany
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2020 – today
- 2026
[i8]Tin Hadzi Veljkovic, Erik J. Bekkers, Michael Tiemann, Jan-Willem van de Meent:
CORDS: Continuous Representations of Discrete Structures. CoRR abs/2601.21583 (2026)- 2025
- [c6]Jens Dörpinghaus, Michael Tiemann:
Large Language Models in Labor Market Research Data Management: Potentials and Limitations. LLMs4RDM@INFORMATIK 2025: 31-36 - 2023
- [c5]Katharina Ensinger, Sebastian Ziesche, Barbara Rakitsch, Michael Tiemann, Sebastian Trimpe:
Combining Slow and Fast: Complementary Filtering for Dynamics Learning. AAAI 2023: 7476-7484 - [c4]Katharina Ott, Michael Tiemann, Philipp Hennig, François-Xavier Briol:
Baysian numerical integration with neural networks. UAI 2023: 1606-1617 - [i7]Katharina Ensinger, Sebastian Ziesche, Barbara Rakitsch, Michael Tiemann, Sebastian Trimpe:
Combining Slow and Fast: Complementary Filtering for Dynamics Learning. CoRR abs/2302.13754 (2023) - [i6]Katharina Ott, Michael Tiemann, Philipp Hennig, François-Xavier Briol:
Bayesian Numerical Integration with Neural Networks. CoRR abs/2305.13248 (2023) - [i5]Katharina Ott, Michael Tiemann, Philipp Hennig:
Uncertainty and Structure in Neural Ordinary Differential Equations. CoRR abs/2305.13290 (2023) - 2022
- [c3]Katharina Ensinger, Friedrich Solowjow, Sebastian Ziesche, Michael Tiemann, Sebastian Trimpe:
Structure-Preserving Gaussian Process Dynamics. ECML/PKDD (5) 2022: 140-156 - [i4]David Duvenaud, Markus Heinonen, Michael Tiemann, Max Welling:
Differential Equations and Continuous-Time Deep Learning (Dagstuhl Seminar 22332). Dagstuhl Reports 12(8): 20-30 (2022) - 2021
- [c2]Katharina Ott, Prateek Katiyar, Philipp Hennig, Michael Tiemann:
ResNet After All: Neural ODEs and Their Numerical Solution. ICLR 2021 - [i3]Katharina Ensinger, Friedrich Solowjow, Michael Tiemann, Sebastian Trimpe:
Symplectic Gaussian Process Dynamics. CoRR abs/2102.01606 (2021) - 2020
- [c1]Hans Kersting, Nicholas Krämer, Martin Schiegg, Christian Daniel, Michael Tiemann, Philipp Hennig:
Differentiable Likelihoods for Fast Inversion of 'Likelihood-Free' Dynamical Systems. ICML 2020: 5198-5208 - [i2]Hans Kersting, Nicholas Krämer, Martin Schiegg, Christian Daniel, Michael Tiemann, Philipp Hennig:
Differentiable Likelihoods for Fast Inversion of 'Likelihood-Free' Dynamical Systems. CoRR abs/2002.09301 (2020) - [i1]Katharina Ott, Prateek Katiyar, Philipp Hennig, Michael Tiemann:
When are Neural ODE Solutions Proper ODEs? CoRR abs/2007.15386 (2020)
Coauthor Index
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