Active Uncertainty Calibration in Bayesian ODE Solvers. - Hans Kersting; Philipp Hennig (UAI, 2016)

Bayesian Filtering for ODEs with Bounded Derivatives. - Emilia Magnani; Hans Kersting; Michael Schober; Philipp Hennig (CoRR, 2017)

Probabilistic solutions to ordinary differential equations as nonlinear Bayesian filtering: a new perspective. - Filip Tronarp; Hans Kersting; Simo Särkkä; Philipp Hennig (Stat. Comput., 2019)

Differentiable Likelihoods for Fast Inversion of 'Likelihood-Free' Dynamical Systems. - Hans Kersting; Nicholas Krämer; Martin Schiegg; Christian Daniel; Michael Tiemann 001; Philipp Hennig (ICML, 2020)

A Fourier State Space Model for Bayesian ODE Filters. - Hans Kersting; Maren Mahsereci (CoRR, 2020)

Convergence rates of Gaussian ODE filters. - Hans Kersting; Timothy John Sullivan; Philipp Hennig (Stat. Comput., 2020)

Anticorrelated Noise Injection for Improved Generalization. - Antonio Orvieto; Hans Kersting; Frank Proske; Francis R. Bach; Aurélien Lucchi (ICML, 2022)

On the Theoretical Properties of Noise Correlation in Stochastic Optimization. - Aurélien Lucchi; Frank Proske; Antonio Orvieto; Francis R. Bach; Hans Kersting (NeurIPS, 2022)

Explicit Regularization in Overparametrized Models via Noise Injection. - Antonio Orvieto; Anant Raj; Hans Kersting; Francis R. Bach (AISTATS, 2023)

An SDE for Modeling SAM: Theory and Insights. - Enea Monzio Compagnoni; Luca Biggio; Antonio Orvieto; Frank Norbert Proske; Hans Kersting; Aurélien Lucchi (ICML, 2023)

SDEs for Minimax Optimization. - Enea Monzio Compagnoni; Antonio Orvieto; Hans Kersting; Frank Proske; Aurélien Lucchi (AISTATS, 2024)