The Sensorimotor Loop as a Dynamical System: How Regular Motion Primitives May Emerge from Self-Organized Limit Cycles. - Bulcsú Sándor; Tim Jahn; Laura Martin 001; Claudius Gros (Frontiers Robotics AI, 2015)

On the Discrepancy Principle for Stochastic Gradient Descent. - Tim Jahn; Bangti Jin (CoRR, 2020)

Regularising linear inverse problems under unknown non-Gaussian white noise. - Bastian Harrach; Tim Jahn; Roland Potthast (CoRR, 2020)

Beyond the Bakushinkii veto: regularising linear inverse problems without knowing the noise distribution. - Bastian Harrach; Tim Jahn; Roland Potthast (Numerische Mathematik, 2020)

Increasing the relative smoothness of stochastically sampled data. - Tim Jahn (CoRR, 2021)

Optimal Convergence of the Discrepancy Principle for polynomially and exponentially ill-posed Operators under White Noise. - Tim Jahn (CoRR, 2021)

Regularising linear inverse problems under unknown non-Gaussian noise - Tim Jahn (2021)

A Probabilistic Oracle Inequality and Quantification of Uncertainty of a modified Discrepancy Principle for Statistical Inverse Problems. - Tim Jahn (CoRR, 2022)

Discretisation-adaptive regularisation of statistical inverse problems. - Tim Jahn (CoRR, 2022)

Noise level free regularisation of general linear inverse problems under unconstrained white noise. - Tim Jahn (CoRR, 2022)

Noise Level Free Regularization of General Linear Inverse Problems under Unconstrained White Noise. - Tim Jahn (SIAM/ASA J. Uncertain. Quantification, 2023)

Efficient solution of ill-posed integral equations through averaging. - Michael Griebel; Tim Jahn (CoRR, 2024)

Early Stopping of Untrained Convolutional Neural Networks. - Tim Jahn; Bangti Jin (SIAM J. Imaging Sci., 2024)

Fast Summation of Radial Kernels via QMC Slicing. - Johannes Hertrich; Tim Jahn; Michael Quellmalz (ICLR, 2025)

Convergence of generalized cross-validation with applications to ill-posed integral equations. - Tim Jahn; Mikhail Kirilin (CoRR, 2025)