Jonathan Wenger

21 papers A* 4A 3Journal 13

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Accelerating Non-Conjugate Gaussian Processes By Trading Off Computation For Uncertainty. Trans. Mach. Learn. Res. Lukas Tatzel, Jonathan Wenger, Frank Schneider, Philipp Hennig
2025	A	`conf`	Computation-Aware Kalman Filtering and Smoothing. AISTATS Marvin Pförtner, Jonathan Wenger, Jon Cockayne, Philipp Hennig
2025	J	`jnl`	Variational Deep Learning via Implicit Regularization. CoRR Jonathan Wenger, Beau Coker, Juraj Marusic, John P. Cunningham
2024	A*	`conf`	Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference. NeurIPS Jonathan Wenger, Kaiwen Wu, Philipp Hennig, Jacob R. Gardner, Geoff Pleiss, John P. Cunningham
2024	J	`jnl`	Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference. CoRR Jonathan Wenger, Kaiwen Wu, Philipp Hennig, Jacob R. Gardner, Geoff Pleiss, John P. Cunningham
2024	J	`jnl`	Computation-Aware Kalman Filtering and Smoothing. CoRR Marvin Pförtner, Jonathan Wenger, Jon Cockayne, Philipp Hennig
2024	A	`conf`	Large-Scale Gaussian Processes via Alternating Projection. AISTATS Kaiwen Wu, Jonathan Wenger, Haydn Thomas Jones, Geoff Pleiss, Jacob R. Gardner
2023	J	`jnl`	Accelerating Generalized Linear Models by Trading off Computation for Uncertainty. CoRR Lukas Tatzel, Jonathan Wenger, Frank Schneider, Philipp Hennig
2023	J	`jnl`	Large-Scale Gaussian Processes via Alternating Projection. CoRR Kaiwen Wu, Jonathan Wenger, Haydn Thomas Jones, Geoff Pleiss, Jacob R. Gardner
2023	J	`jnl`	On the Disconnect Between Theory and Practice of Overparametrized Neural Networks. CoRR Jonathan Wenger, Felix Dangel, Agustinus Kristiadi
2023	—	`—`	Probabilistic Numerical Linear Algebra for Machine Learning Jonathan Wenger
2022	J	`jnl`	Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers. CoRR Marvin Pförtner, Ingo Steinwart, Philipp Hennig, Jonathan Wenger
2022	A*	`conf`	Posterior and Computational Uncertainty in Gaussian Processes. NeurIPS Jonathan Wenger, Geoff Pleiss, Marvin Pförtner, Philipp Hennig, John P. Cunningham
2022	J	`jnl`	Posterior and Computational Uncertainty in Gaussian Processes. CoRR Jonathan Wenger, Geoff Pleiss, Marvin Pförtner, Philipp Hennig, John P. Cunningham
2022	A*	`conf`	Preconditioning for Scalable Gaussian Process Hyperparameter Optimization. ICML Jonathan Wenger, Geoff Pleiss, Philipp Hennig, John P. Cunningham, Jacob R. Gardner
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`	Reducing the Variance of Gaussian Process Hyperparameter Optimization with Preconditioning. CoRR Jonathan Wenger, Geoff Pleiss, Philipp Hennig, John P. Cunningham, Jacob R. Gardner
2020	A	`conf`	Non-Parametric Calibration for Classification. AISTATS Jonathan Wenger, Hedvig Kjellström, Rudolph Triebel
2020	A*	`conf`	Probabilistic Linear Solvers for Machine Learning. NeurIPS Jonathan Wenger, Philipp Hennig
2020	J	`jnl`	Probabilistic Linear Solvers for Machine Learning. CoRR Jonathan Wenger, Philipp Hennig
2019	J	`jnl`	Non-Parametric Calibration for Classification. CoRR Jonathan Wenger, Hedvig Kjellström, Rudolph Triebel