Hans Kersting

According to our database, Hans Kersting authored at least 11 papers between 2016 and 2024.

Collaborative distances:

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

2024

SDEs for Minimax Optimization.

Enea Monzio Compagnoni, Antonio Orvieto, Hans Kersting, Frank Norbert Proske, Aurélien Lucchi

CoRR, 2024

2023

An SDE for Modeling SAM: Theory and Insights.

Enea Monzio Compagnoni, Luca Biggio, Antonio Orvieto, Frank Norbert Proske, Hans Kersting, Aurélien Lucchi

Proceedings of the International Conference on Machine Learning, 2023

Explicit Regularization in Overparametrized Models via Noise Injection.

Antonio Orvieto, Anant Raj, Hans Kersting, Francis R. Bach

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

On the Theoretical Properties of Noise Correlation in Stochastic Optimization.

Aurélien Lucchi, Frank Proske, Antonio Orvieto, Francis R. Bach, Hans Kersting

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Anticorrelated Noise Injection for Improved Generalization.

Antonio Orvieto, Hans Kersting, Frank Proske, Francis R. Bach, Aurélien Lucchi

Proceedings of the International Conference on Machine Learning, 2022

2020

Convergence rates of Gaussian ODE filters.

Hans Kersting, Timothy John Sullivan, Philipp Hennig

Stat. Comput., 2020

A Fourier State Space Model for Bayesian ODE Filters.

Hans Kersting, Maren Mahsereci

CoRR, 2020

Differentiable Likelihoods for Fast Inversion of 'Likelihood-Free' Dynamical Systems.

Hans Kersting, Nicholas Krämer, Martin Schiegg, Christian Daniel, Michael Tiemann, Philipp Hennig

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Probabilistic solutions to ordinary differential equations as nonlinear Bayesian filtering: a new perspective.

Filip Tronarp, Hans Kersting, Simo Särkkä, Philipp Hennig

Stat. Comput., 2019

2017

Bayesian Filtering for ODEs with Bounded Derivatives.

Emilia Magnani, Hans Kersting, Michael Schober, Philipp Hennig

CoRR, 2017

2016

Active Uncertainty Calibration in Bayesian ODE Solvers.

Hans Kersting, Philipp Hennig

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016