Krämer, Nicholas

10 publications

TMLR 2025 Approximate Bayesian Neural Operators: Uncertainty Quantification for Parametric PDEs Emilia Magnani, Nicholas Krämer, Runa Eschenhagen, Lorenzo Rosasco, Philipp Hennig

TMLR 2025 Numerically Robust Fixed-Point Smoothing Without State Augmentation Nicholas Krämer

NeurIPS 2025 VIKING: Deep Variational Inference with Stochastic Projections Samuel G. Fadel, Hrittik Roy, Nicholas Krämer, Yevgen Zainchkovskyy, Stas Syrota, Alejandro Valverde Mahou, Carl Henrik Ek, Søren Hauberg

NeurIPS 2024 Gradients of Functions of Large Matrices Nicholas Krämer, Pablo Moreno-Muñoz, Hrittik Roy, Søren Hauberg

JMLR 2024 Stable Implementation of Probabilistic ODE Solvers Nicholas Krämer, Philipp Hennig

AISTATS 2022 Probabilistic Numerical Method of Lines for Time-Dependent Partial Differential Equations Nicholas Krämer, Jonathan Schmidt, Philipp Hennig

ICML 2022 Probabilistic ODE Solutions in Millions of Dimensions Nicholas Krämer, Nathanael Bosch, Jonathan Schmidt, Philipp Hennig

NeurIPS 2021 A Probabilistic State Space Model for Joint Inference from Differential Equations and Data Jonathan Schmidt, Nicholas Krämer, Philipp Hennig

NeurIPS 2021 Linear-Time Probabilistic Solution of Boundary Value Problems Nicholas Krämer, Philipp Hennig

ICML 2020 Differentiable Likelihoods for Fast Inversion of ’Likelihood-Free’ Dynamical Systems Hans Kersting, Nicholas Krämer, Martin Schiegg, Christian Daniel, Michael Tiemann, Philipp Hennig