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Jonathan Wenger
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Non-Parametric Calibration for Classification
J Wenger, H Kjellström, R Triebel
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
902020
Preconditioning for Scalable Gaussian Process Hyperparameter Optimization
J Wenger, G Pleiss, P Hennig, JP Cunningham, JR Gardner
International Conference on Machine Learning (ICML), 2022
26*2022
Physics-informed Gaussian Process Regression Generalizes Linear PDE Solvers
M Pförtner, I Steinwart, P Hennig, J Wenger
arXiv preprint arXiv:2212.12474, 2022
182022
ProbNum: Probabilistic Numerics in Python
J Wenger, N Krämer, M Pförtner, J Schmidt, N Bosch, N Effenberger, ...
arXiv preprint arXiv:2112.02100, 2021
162021
Probabilistic Linear Solvers for Machine Learning
J Wenger, P Hennig
Advances in Neural Information Processing Systems (NeurIPS), 2020
162020
Posterior and Computational Uncertainty in Gaussian Processes
J Wenger, G Pleiss, M Pförtner, P Hennig, JP Cunningham
Advances in Neural Information Processing Systems (NeurIPS), 2022
92022
Large-Scale Gaussian Processes via Alternating Projection
K Wu, J Wenger, H Jones, G Pleiss, JR Gardner
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
22024
On the Disconnect Between Theory and Practice of Overparametrized Neural Networks
J Wenger, F Dangel, A Kristiadi
arXiv preprint arXiv:2310.00137, 2023
12023
Computation-Aware Kalman Filtering and Smoothing
M Pförtner, J Wenger, J Cockayne, P Hennig
arXiv e-prints, arXiv: 2405.08971, 2024
2024
Accelerating Generalized Linear Models by Trading off Computation for Uncertainty
L Tatzel, J Wenger, F Schneider, P Hennig
arXiv preprint arXiv:2310.20285, 2023
2023
Probabilistic Numerical Linear Algebra for Machine Learning
J Wenger
Universität Tübingen, 2023
2023
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Articles 1–11