Nathanael Bosch

According to our database, Nathanael Bosch authored at least 12 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

ProbNumDiffEq.jl: Probabilistic Numerical Solvers for Ordinary Differential Equations in Julia.

Nathanael Bosch

J. Open Source Softw., 2024

Parallel-in-Time Probabilistic Numerical ODE Solvers.

Nathanael Bosch, Adrien Corenflos, Fatemeh Yaghoobi, Filip Tronarp, Philipp Hennig, Simo Särkkä

J. Mach. Learn. Res., 2024

Efficient Weight-Space Laplace-Gaussian Filtering and Smoothing for Sequential Deep Learning.

Joanna Sliwa, Frank Schneider, Nathanael Bosch, Agustinus Kristiadi, Philipp Hennig

CoRR, 2024

Probabilistic ODE solvers for integration error-aware numerical optimal control.

Amon Lahr, Filip Tronarp, Nathanael Bosch, Jonathan Schmidt, Philipp Hennig, Melanie N. Zeilinger

Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

Diffusion Tempering Improves Parameter Estimation with Probabilistic Integrators for Ordinary Differential Equations.

Jonas Beck, Nathanael Bosch, Michael Deistler, Kyra L. Kadhim, Jakob H. Macke, Philipp Hennig, Philipp Berens

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Probabilistic Exponential Integrators.

Nathanael Bosch, Philipp Hennig, Filip Tronarp

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Fenrir: Physics-Enhanced Regression for Initial Value Problems.

Filip Tronarp, Nathanael Bosch, Philipp Hennig

Proceedings of the International Conference on Machine Learning, 2022

Probabilistic ODE Solutions in Millions of Dimensions.

Nicholas Krämer, Nathanael Bosch, Jonathan Schmidt, Philipp Hennig

Proceedings of the International Conference on Machine Learning, 2022

Pick-and-Mix Information Operators for Probabilistic ODE Solvers.

Nathanael Bosch, Filip Tronarp, Philipp Hennig

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

ProbNum: Probabilistic Numerics in Python.

Jonathan Wenger, Nicholas Krämer, Marvin Pförtner, Jonathan Schmidt, Nathanael Bosch, Nina Effenberger, Johannes Zenn, Alexandra Gessner, Toni Karvonen, François-Xavier Briol, Maren Mahsereci, Philipp Hennig

CoRR, 2021

Calibrated Adaptive Probabilistic ODE Solvers.

Nathanael Bosch, Philipp Hennig, Filip Tronarp

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Planning from Images with Deep Latent Gaussian Process Dynamics.

Nathanael Bosch, Jan Achterhold, Laura Leal-Taixé, Jörg Stückler

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020