Jonathan Wenger

According to our database, Jonathan Wenger authored at least 15 papers between 2020 and 2025.

Collaborative distances:

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

2025

Variational Deep Learning via Implicit Regularization.

Jonathan Wenger, Beau Coker, Juraj Marusic, John P. Cunningham

CoRR, May, 2025

Accelerating Non-Conjugate Gaussian Processes By Trading Off Computation For Uncertainty.

Lukas Tatzel, Jonathan Wenger, Frank Schneider, Philipp Hennig

Trans. Mach. Learn. Res., 2025

Computation-Aware Kalman Filtering and Smoothing.

Marvin Pförtner, Jonathan Wenger, Jon Cockayne, Philipp Hennig

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference.

Jonathan Wenger, Kaiwen Wu, Philipp Hennig, Jacob R. Gardner, Geoff Pleiss, John P. Cunningham

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Large-Scale Gaussian Processes via Alternating Projection.

Kaiwen Wu, Jonathan Wenger, Haydn Thomas Jones, Geoff Pleiss, Jacob R. Gardner

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Probabilistic Numerical Linear Algebra for Machine Learning

Jonathan Wenger

PhD thesis, 2023

Accelerating Generalized Linear Models by Trading off Computation for Uncertainty.

Lukas Tatzel, Jonathan Wenger, Frank Schneider, Philipp Hennig

CoRR, 2023

On the Disconnect Between Theory and Practice of Overparametrized Neural Networks.

Jonathan Wenger, Felix Dangel, Agustinus Kristiadi

CoRR, 2023

2022

Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers.

Marvin Pförtner, Ingo Steinwart, Philipp Hennig, Jonathan Wenger

CoRR, 2022

Posterior and Computational Uncertainty in Gaussian Processes.

Jonathan Wenger, Geoff Pleiss, Marvin Pförtner, Philipp Hennig, John P. Cunningham

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

Preconditioning for Scalable Gaussian Process Hyperparameter Optimization.

Jonathan Wenger, Geoff Pleiss, Philipp Hennig, John P. Cunningham, Jacob R. Gardner

Proceedings of the International Conference on Machine Learning, 2022

2021

ProbNum: Probabilistic Numerics in Python.

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

CoRR, 2021

Reducing the Variance of Gaussian Process Hyperparameter Optimization with Preconditioning.

Jonathan Wenger, Geoff Pleiss, Philipp Hennig, John P. Cunningham, Jacob R. Gardner

CoRR, 2021

2020

Probabilistic Linear Solvers for Machine Learning.

Jonathan Wenger, Philipp Hennig

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Non-Parametric Calibration for Classification.

Jonathan Wenger, Hedvig Kjellström, Rudolph Triebel

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020