Non-Parametric Calibration for Classification J Wenger, H Kjellström, R Triebel International Conference on Artificial Intelligence and Statistics (AISTATS), 2020 | 99 | 2020 |
Preconditioning for Scalable Gaussian Process Hyperparameter Optimization J Wenger, G Pleiss, P Hennig, JP Cunningham, JR Gardner International Conference on Machine Learning (ICML), 2022 | 30* | 2022 |
Physics-informed Gaussian Process Regression Generalizes Linear PDE Solvers M Pförtner, I Steinwart, P Hennig, J Wenger arXiv preprint arXiv:2212.12474, 2022 | 20 | 2022 |
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 | 18 | 2022 |
ProbNum: Probabilistic Numerics in Python J Wenger, N Krämer, M Pförtner, J Schmidt, N Bosch, N Effenberger, ... arXiv preprint arXiv:2112.02100, 2021 | 17 | 2021 |
Probabilistic Linear Solvers for Machine Learning J Wenger, P Hennig Advances in Neural Information Processing Systems (NeurIPS), 2020 | 17 | 2020 |
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 | 5 | 2024 |
On the Disconnect Between Theory and Practice of Neural Networks: Limits of the Neural Tangent Kernel Perspective J Wenger, F Dangel, A Kristiadi arXiv preprint arXiv:2310.00137, 2023 | 3* | 2023 |
Accelerating Generalized Linear Models by Trading off Computation for Uncertainty L Tatzel, J Wenger, F Schneider, P Hennig arXiv preprint arXiv:2310.20285, 2023 | 1 | 2023 |
Computation-Aware Kalman Filtering and Smoothing M Pförtner, J Wenger, J Cockayne, P Hennig arXiv preprint arXiv:2405.08971, 2024 | | 2024 |
Probabilistic Numerical Linear Algebra for Machine Learning J Wenger Universität Tübingen, 2023 | | 2023 |