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2020 – today
- 2024
[c5]Kaiwen Wu, Jonathan Wenger, Haydn T. Jones, Geoff Pleiss, Jacob R. Gardner:
Large-Scale Gaussian Processes via Alternating Projection. AISTATS 2024: 2620-2628- [i10]Marvin Pförtner, Jonathan Wenger, Jon Cockayne, Philipp Hennig:
Computation-Aware Kalman Filtering and Smoothing. CoRR abs/2405.08971 (2024) - 2023
- [b1]Jonathan Wenger:
Probabilistic Numerical Linear Algebra for Machine Learning. Tübingen University, Germany, 2023 - [i9]Jonathan Wenger, Felix Dangel, Agustinus Kristiadi:
On the Disconnect Between Theory and Practice of Overparametrized Neural Networks. CoRR abs/2310.00137 (2023) - [i8]Kaiwen Wu, Jonathan Wenger, Haydn Jones, Geoff Pleiss, Jacob R. Gardner:
Large-Scale Gaussian Processes via Alternating Projection. CoRR abs/2310.17137 (2023) - [i7]Lukas Tatzel, Jonathan Wenger, Frank Schneider, Philipp Hennig
:
Accelerating Generalized Linear Models by Trading off Computation for Uncertainty. CoRR abs/2310.20285 (2023) - 2022
- [c4]Jonathan Wenger, Geoff Pleiss, Philipp Hennig, John P. Cunningham, Jacob R. Gardner:
Preconditioning for Scalable Gaussian Process Hyperparameter Optimization. ICML 2022: 23751-23780 - [c3]Jonathan Wenger, Geoff Pleiss, Marvin Pförtner, Philipp Hennig, John P. Cunningham:
Posterior and Computational Uncertainty in Gaussian Processes. NeurIPS 2022 - [i6]Jonathan Wenger, Geoff Pleiss, Marvin Pförtner, Philipp Hennig, John P. Cunningham:
Posterior and Computational Uncertainty in Gaussian Processes. CoRR abs/2205.15449 (2022) - [i5]Marvin Pförtner, Ingo Steinwart, Philipp Hennig, Jonathan Wenger:
Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers. CoRR abs/2212.12474 (2022) - 2021
- [i4]Jonathan Wenger, Geoff Pleiss, Philipp Hennig, John P. Cunningham, Jacob R. Gardner:
Reducing the Variance of Gaussian Process Hyperparameter Optimization with Preconditioning. CoRR abs/2107.00243 (2021) - [i3]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:
ProbNum: Probabilistic Numerics in Python. CoRR abs/2112.02100 (2021) - 2020
- [c2]Jonathan Wenger, Hedvig Kjellström, Rudolph Triebel:
Non-Parametric Calibration for Classification. AISTATS 2020: 178-190 - [c1]Jonathan Wenger, Philipp Hennig:
Probabilistic Linear Solvers for Machine Learning. NeurIPS 2020 - [i2]Jonathan Wenger, Philipp Hennig:
Probabilistic Linear Solvers for Machine Learning. CoRR abs/2010.09691 (2020)
2010 – 2019
- 2019
- [i1]Jonathan Wenger, Hedvig Kjellström, Rudolph Triebel:
Non-Parametric Calibration for Classification. CoRR abs/1906.04933 (2019)
Coauthor Index
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