| Julia for biologists E Roesch, JG Greener, AL MacLean, H Nassar, C Rackauckas, TE Holy, ... Nature methods 20 (5), 655-664, 2023 | 22 | 2023 |
| Collocation based training of neural ordinary differential equations E Roesch, C Rackauckas, MPH Stumpf Statistical Applications in Genetics and Molecular Biology 20 (2), 37-49, 2021 | 20 | 2021 |
| GpABC: a Julia package for approximate Bayesian computation with Gaussian process emulation E Tankhilevich, J Ish-Horowicz, T Hameed, E Roesch, I Kleijn, ... Bioinformatics 36 (10), 3286-3287, 2020 | 16 | 2020 |
| Parameter inference in dynamical systems with co-dimension 1 bifurcations E Roesch, MPH Stumpf Royal Society Open Science 6 (10), 190747, 2019 | 10 | 2019 |
| Uncertainty in cell fate decision making: Lessons from potential landscapes of bifurcation systems A Guillemin, E Roesch, MPH Stumpf bioRxiv, 2021.01. 03.425143, 2021 | 1 | 2021 |
| Julia for biologists (vol 20, pg 655, 2023) E Roesch, JG Greener, AL MacLean, H Nassar, C Rackauckas, TE Holy, ... NATURE METHODS 20 (5), 771-771, 2023 | | 2023 |
| Author Correction: Julia for biologists E Roesch, JG Greener, AL MacLean, H Nassar, C Rackauckas, TE Holy, ... Nature Methods 20 (5), 771-771, 2023 | | 2023 |
| Stably Accelerating Stiff Quantitative Systems Pharmacology Models: Continuous-Time Echo State Networks as Implicit Machine Learning C Rackauckas, E Roesch | | 2022 |
Michael P H StumpfProfessor of Theoretical Systems Biology, University of MelbourneVerified email at unimelb.edu.au
