Nicholas Krämer

27 papers A* 5A 1Journal 20Unranked 1
YearRankTypeTitle / Venue / Authors
2025 — conf
Adaptive Probabilistic ODE Solvers Without Adaptive Memory Requirements.
ProbNum
Nicholas Krämer
2025 J jnl
Approximate Bayesian Neural Operators: Uncertainty Quantification for Parametric PDEs.
Trans. Mach. Learn. Res.
Emilia Magnani, Nicholas Krämer, Runa Eschenhagen, Lorenzo Rosasco, Philipp Hennig
2025 J jnl
Matrix-Free Least Squares Solvers: Values, Gradients, and What to Do With Them.
CoRR
Hrittik Roy, Søren Hauberg, Nicholas Krämer
2025 J jnl
Numerically Robust Fixed-Point Smoothing Without State Augmentation.
Trans. Mach. Learn. Res.
Nicholas Krämer
2025 J jnl
Numerically robust Gaussian state estimation with singular observation noise.
CoRR
Nicholas Krämer, Filip Tronarp
2025 J jnl
VIKING: Deep variational inference with stochastic projections.
CoRR
Samuel G. Fadel, Hrittik Roy, Nicholas Krämer, Yevgen Zainchkovskyy, Stas Syrota, Alejandro Valverde Mahou, Carl Henrik Ek, Søren Hauberg
2024 J jnl
A tutorial on automatic differentiation with complex numbers.
CoRR
Nicholas Krämer
2024 J jnl
Adaptive Probabilistic ODE Solvers Without Adaptive Memory Requirements.
CoRR
Nicholas Krämer
2024 A* conf
Gradients of Functions of Large Matrices.
NeurIPS
Nicholas Krämer, Pablo Moreno-Muñoz, Hrittik Roy, Søren Hauberg
2024 J jnl
Gradients of Functions of Large Matrices.
CoRR
Nicholas Krämer, Pablo Moreno-Muñoz, Hrittik Roy, Søren Hauberg
2024 J jnl
Numerically Robust Fixed-Point Smoothing Without State Augmentation.
CoRR
Nicholas Krämer
2024 J jnl
Stable Implementation of Probabilistic ODE Solvers.
J. Mach. Learn. Res.
Nicholas Krämer, Philipp Hennig
2022 J jnl
Approximate Bayesian Neural Operators: Uncertainty Quantification for Parametric PDEs.
CoRR
Emilia Magnani, Nicholas Krämer, Runa Eschenhagen, Lorenzo Rosasco, Philipp Hennig
2022 J jnl
Correction to: Probabilistic solvers enable a straight-forward exploration of numerical uncertainty in neuroscience models.
J. Comput. Neurosci.
Jonathan Oesterle, Nicholas Krämer, Philipp Hennig, Philipp Berens
2022 A conf
Probabilistic Numerical Method of Lines for Time-Dependent Partial Differential Equations.
AISTATS
Nicholas Krämer, Jonathan Schmidt, Philipp Hennig
2022 A* conf
Probabilistic ODE Solutions in Millions of Dimensions.
ICML
Nicholas Krämer, Nathanael Bosch, Jonathan Schmidt, Philipp Hennig
2022 J jnl
Probabilistic solvers enable a straight-forward exploration of numerical uncertainty in neuroscience models.
J. Comput. Neurosci.
Jonathan Oesterle, Nicholas Krämer, Philipp Hennig, Philipp Berens
2021 A* conf
A Probabilistic State Space Model for Joint Inference from Differential Equations and Data.
NeurIPS
Jonathan Schmidt, Nicholas Krämer, Philipp Hennig
2021 J jnl
A Probabilistic State Space Model for Joint Inference from Differential Equations and Data.
CoRR
Jonathan Schmidt, Nicholas Krämer, Philipp Hennig
2021 A* conf
Linear-Time Probabilistic Solution of Boundary Value Problems.
NeurIPS
Nicholas Krämer, Philipp Hennig
2021 J jnl
Linear-Time Probabilistic Solutions of Boundary Value Problems.
CoRR
Nicholas Krämer, Philipp Hennig
2021 J jnl
ProbNum: Probabilistic Numerics in Python.
CoRR
Jonathan Wenger, Nicholas Krämer, Marvin Pförtner, Jonathan Schmidt, Nathanael Bosch, Nina Effenberger, Johannes Zenn, Alexandra Gessner, Toni Karvonen, François-Xavier Briol, Maren Mahsereci, Philipp Hennig
2021 J jnl
Probabilistic Numerical Method of Lines for Time-Dependent Partial Differential Equations.
CoRR
Nicholas Krämer, Jonathan Schmidt, Philipp Hennig
2021 J jnl
Probabilistic ODE Solutions in Millions of Dimensions.
CoRR
Nicholas Krämer, Nathanael Bosch, Jonathan Schmidt, Philipp Hennig
2020 A* conf
Differentiable Likelihoods for Fast Inversion of 'Likelihood-Free' Dynamical Systems.
ICML
Hans Kersting, Nicholas Krämer, Martin Schiegg, Christian Daniel, Michael Tiemann, Philipp Hennig
2020 J jnl
Differentiable Likelihoods for Fast Inversion of 'Likelihood-Free' Dynamical Systems.
CoRR
Hans Kersting, Nicholas Krämer, Martin Schiegg, Christian Daniel, Michael Tiemann, Philipp Hennig
2020 J jnl
Stable Implementation of Probabilistic ODE Solvers.
CoRR
Nicholas Krämer, Philipp Hennig