Adapting the Secretary Hiring Problem for Optimal Hot-Cold Tier Placement Under Top-K Workloads. - Ben Blamey; Fredrik Wrede; Johan Karlsson; Andreas Hellander; Salman Toor (CCGRID, 2019)

Smart computational exploration of stochastic gene regulatory network models using human-in-the-loop semi-supervised learning. - Fredrik Wrede; Andreas Hellander (Bioinform., 2019)

Epidemiological modeling in StochSS Live! - Richard M. Jiang 002; Bruno Jacob; Matthew Geiger; Sean Matthew; Bryan Rumsey; Prashant Singh; Fredrik Wrede; Tau-Mu Yi; Brian Drawert; Andreas Hellander; Linda R. Petzold (Bioinform., 2021)

Scalable machine learning-assisted model exploration and inference using Sciope. - Prashant Singh; Fredrik Wrede; Andreas Hellander (Bioinform., 2021)

Accelerated regression-based summary statistics for discrete stochastic systems via approximate simulators. - Richard M. Jiang 002; Fredrik Wrede; Prashant Singh; Andreas Hellander; Linda R. Petzold (BMC Bioinform., 2021)

Large-scale simulation-based experiments with stochastic models using machine learning-assisted approaches: Applications in systems biology using Markov jump processes. - Fredrik Wrede (2021)

Robust and integrative Bayesian neural networks for likelihood-free parameter inference. - Fredrik Wrede; Robin Eriksson; Richard M. Jiang 002; Linda R. Petzold; Stefan Engblom; Andreas Hellander; Prashant Singh (IJCNN, 2022)

Identification of dynamic mass-action biochemical reaction networks using sparse Bayesian methods. - Richard M. Jiang 002; Prashant Singh; Fredrik Wrede; Andreas Hellander; Linda R. Petzold (PLoS Comput. Biol., 2022)

Convolutional Neural Networks as Summary Statistics for Approximate Bayesian Computation. - Mattias Åkesson; Prashant Singh; Fredrik Wrede; Andreas Hellander (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)