| Linearly constrained Gaussian processes C Jidling, N Wahlström, A Wills, TB Schön Advances in Neural Information Processing Systems 30, 2017 | 82 | 2017 |
| The effect of interventions on COVID-19 K Soltesz, F Gustafsson, T Timpka, J Jaldén, C Jidling, A Heimerson, ... Nature 588 (7839), E26-E28, 2020 | 65 | 2020 |
| Probabilistic modelling and reconstruction of strain C Jidling, J Hendriks, N Wahlström, A Gregg, TB Schön, C Wensrich, ... Nuclear Instruments and Methods in Physics Research Section B: Beam …, 2018 | 34 | 2018 |
| Linearly constrained neural networks J Hendriks, C Jidling, A Wills, T Schön arXiv preprint arXiv:2002.01600, 2020 | 16 | 2020 |
| Probabilistic approach to limited-data computed tomography reconstruction Z Purisha, C Jidling, N Wahlström, TB Schön, S Särkkä Inverse Problems 35 (10), 105004, 2019 | 15 | 2019 |
| Evaluating the squared-exponential covariance function in Gaussian processes with integral observations JN Hendriks, C Jidling, A Wills, TB Schön arXiv preprint arXiv:1812.07319, 2018 | 6 | 2018 |
| On the sensitivity of non-pharmaceutical intervention models for SARS-CoV-2 spread estimation K Soltesz, F Gustafsson, T Timpka, J Jaldén, C Jidling, A Heimerson, ... medRxiv, 2020 | 5 | 2020 |
| Sensitivity analysis of the effects of non-pharmaceutical interventions on COVID-19 in Europe K Soltesz, F Gustafsson, T Timpka, J Jaldén, C Jidling, A Heimerson, ... medRxiv, 2020 | 4 | 2020 |
| A fast quasi-Newton-type method for large-scale stochastic optimisation A Wills, TB Schön, C Jidling IFAC-PapersOnLine 53 (2), 1249-1254, 2020 | 4 | 2020 |
| Modelling bivariate distributions using kernel density estimation A Bilock, C Jidling, Y Rydin Project course in Computational Science, 2016 | 4 | 2016 |
| Neutron transmission strain tomography for non-constant stress-free lattice spacing JN Hendriks, C Jidling, TB Schön, A Wills, CM Wensrich, EH Kisi Nuclear Instruments and Methods in Physics Research Section B: Beam …, 2019 | 3 | 2019 |
| A Probabilistically Motivated Learning Rate Adaptation for Stochastic Optimization F de Roos, C Jidling, A Wills, T Schön, P Hennig arXiv preprint arXiv:2102.10880, 2021 | 2 | 2021 |
| Deep kernel learning for integral measurements C Jidling, J Hendriks, TB Schön, A Wills arXiv preprint arXiv:1909.01844, 2019 | 2 | 2019 |
| Incorporating Sum Constraints into Multitask Gaussian Processes P Pilar, C Jidling, TB Schön, N Wahlström arXiv preprint arXiv:2202.01793, 2022 | 1 | 2022 |
| Tailoring Gaussian processes for tomographic reconstruction C Jidling Uppsala University, 2019 | 1 | 2019 |
| Strain Field Modelling using Gaussian Processes C Jidling | 1 | 2017 |
| Memory efficient constrained optimization of scanning-beam lithography C Jidling, AJ Fleming, AG Wills, TB Schön Optics Express 30 (12), 20564-20579, 2022 | | 2022 |
| Tailoring Gaussian processes and large-scale optimisation C Jidling Acta Universitatis Upsaliensis, 2022 | | 2022 |
| Carl Jidling, Niklas Wahlström, Adrian Wills, and Thomas B. Schön. C Jidling Tailoring Gaussian processes for tomo-graphic reconstruction, 63, 2019 | | 2019 |
| Carl Jidling, Johannes Hendriks, Niklas Wahlström, Alexander Gregg, Thomas B. Schön, Christopher Wensrich, and Adrian Wills. C Jidling Tailoring Gaussian processes for tomo-graphic reconstruction, 89, 2019 | | 2019 |
