| Convolutional neural networks as summary statistics for approximate Bayesian computation M Åkesson, P Singh, F Wrede, A Hellander IEEE/ACM Transactions on Computational Biology and Bioinformatics 19 (6 …, 2021 | 39 | 2021 |
| Smart computational exploration of stochastic gene regulatory network models using human-in-the-loop semi-supervised learning F Wrede, A Hellander Bioinformatics 35 (24), 5199-5206, 2019 | 22 | 2019 |
| Epidemiological modeling in StochSS Live! R Jiang, B Jacob, M Geiger, S Matthew, B Rumsey, P Singh, F Wrede, ... Bioinformatics 37 (17), 2787-2788, 2021 | 10 | 2021 |
| Scalable machine learning-assisted model exploration and inference using Sciope P Singh, F Wrede, A Hellander Bioinformatics 37 (2), 279-281, 2021 | 9 | 2021 |
| Robust and integrative Bayesian neural networks for likelihood-free parameter inference F Wrede, R Eriksson, R Jiang, L Petzold, S Engblom, A Hellander, ... 2022 International Joint Conference on Neural Networks (IJCNN), 1-10, 2022 | 8 | 2022 |
| Adapting the secretary hiring problem for optimal hot-cold tier placement under top-K workloads B Blamey, F Wrede, J Karlsson, A Hellander, S Toor 2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid …, 2019 | 8 | 2019 |
| Identification of dynamic mass-action biochemical reaction networks using sparse Bayesian methods R Jiang, P Singh, F Wrede, A Hellander, L Petzold PLoS computational biology 18 (1), e1009830, 2022 | 7 | 2022 |
| Accelerated regression-based summary statistics for discrete stochastic systems via approximate simulators RM Jiang, F Wrede, P Singh, A Hellander, LR Petzold BMC bioinformatics 22 (1), 339, 2021 | 1 | 2021 |
| Large-scale simulation-based experiments with stochastic models using machine learning-assisted approaches: Applications in systems biology using Markov jump processes F Wrede Acta Universitatis Upsaliensis, 2021 | | 2021 |
Andreas HellanderAssociate Professor in Scientific Computing, Division of Scientific Computing, Department of在 it.uu.se 的电子邮件经过验证
