| Alternating linear scheme in a bayesian framework for low-rank tensor approximation C Menzen, M Kok, K Batselier SIAM Journal on scientific Computing 44 (3), A1116-A1144, 2022 | 5 | 2022 |
| Large-scale magnetic field maps using structured kernel interpolation for Gaussian process regression C Menzen, M Fetter, M Kok 2023 26th International Conference on Information Fusion (FUSION), 1-7, 2023 | 3 | 2023 |
| Projecting basis functions with tensor networks for Gaussian process regression C Menzen, E Memmel, K Batselier, M Kok IFAC-PapersOnLine 56 (2), 7288-7293, 2023 | 2 | 2023 |
| Position: Tensor Networks are a Valuable Asset for Green AI E Memmel, C Menzen, J Schuurmans, F Wesel, K Batselier arXiv preprint arXiv:2205.12961, 2022 | 2 | 2022 |
| Tensor network square root Kalman filter for online Gaussian process regression C Menzen, M Kok, K Batselier arXiv preprint arXiv:2409.03276, 2024 | | 2024 |
| Bayesian Framework for a MIMO Volterra Tensor Network E Memmel, C Menzen, K Batselier IFAC-PapersOnLine 56 (2), 7294-7299, 2023 | | 2023 |
| Supervised machine learning with tensor-based kernel machines K Batselier, A Kilic, E Memmel, C Menzen, A Saiapin, F Wesel | | |
| Supervised machine learning with tensor network kernel machines K Batselier, A Kilic, E Memmel, C Menzen, A Saiapin, F Wesel | | |
Kim BatselierDelft University of Technology在 tudelft.nl 的电子邮件经过验证
