Tim Jahn

According to our database, Tim Jahn authored at least 17 papers between 2015 and 2026.

Collaborative distances:

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

2026

On the convergence of an adaptive denoiser driven iterative regularization with early stopping.

Harshit Bajpai, Ankik Kumar Giri, Tim Jahn, Abhinav Jha

CoRR, April, 2026

Prior-Fitted Functional Flow: In-Context Generative Models for Pharmacokinetics.

César Ojeda, Niklas Hartung, Wilhelm Huisinga, Tim Jahn, Purity Kavwele, Marian Klose, Piyush Kumar, Ramsés J. Sánchez, Darius A. Faroughy

CoRR, April, 2026

2025

Convergence of generalized cross-validation with applications to ill-posed integral equations.

Tim Jahn, Mikhail Kirilin

CoRR, June, 2025

Fast Summation of Radial Kernels via QMC Slicing.

Johannes Hertrich, Tim Jahn, Michael Quellmalz

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Early Stopping of Untrained Convolutional Neural Networks.

Tim Jahn, Bangti Jin

SIAM J. Imaging Sci., 2024

Efficient solution of ill-posed integral equations through averaging.

Michael Griebel, Tim Jahn

CoRR, 2024

2023

Noise Level Free Regularization of General Linear Inverse Problems under Unconstrained White Noise.

Tim Jahn

SIAM/ASA J. Uncertain. Quantification, June, 2023

2022

Noise level free regularisation of general linear inverse problems under unconstrained white noise.

Tim Jahn

CoRR, 2022

Discretisation-adaptive regularisation of statistical inverse problems.

Tim Jahn

CoRR, 2022

A Probabilistic Oracle Inequality and Quantification of Uncertainty of a modified Discrepancy Principle for Statistical Inverse Problems.

Tim Jahn

CoRR, 2022

2021

Regularising linear inverse problems under unknown non-Gaussian noise

Tim Jahn

PhD thesis, 2021

Optimal Convergence of the Discrepancy Principle for polynomially and exponentially ill-posed Operators under White Noise.

Tim Jahn

CoRR, 2021

Increasing the relative smoothness of stochastically sampled data.

Tim Jahn

CoRR, 2021

2020

Beyond the Bakushinkii veto: regularising linear inverse problems without knowing the noise distribution.

Bastian Harrach, Tim Jahn, Roland Potthast

Numerische Mathematik, 2020

Regularising linear inverse problems under unknown non-Gaussian white noise.

Bastian Harrach, Tim Jahn, Roland Potthast

CoRR, 2020

On the Discrepancy Principle for Stochastic Gradient Descent.

Tim Jahn, Bangti Jin

CoRR, 2020

2015

The Sensorimotor Loop as a Dynamical System: How Regular Motion Primitives May Emerge from Self-Organized Limit Cycles.

Bulcsú Sándor, Tim Jahn, Laura Martin, Claudius Gros

Frontiers Robotics AI, 2015