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libRoadRunner is a C/C++ software library that supports simulation of SBML based models.. It uses LLVM to generate extremely high-performance code and is the fastest SBML-based simulator currently available. Its main purpose is for use as a reusable library that can be hosted by other applications, particularly on large compute clusters for doing parameter optimization where performance is critical. It also has a set of Python bindings that allow it to be easily used from Python.
References
- ↑ Kevin René Broløs; Meera Vieira Machado; Chris Cave; Jaan Kasak; Valdemar Stentoft-Hansen; Victor Galindo Batanero; Tom Jelen; Casper Wilstrup (2021-04-12). "An Approach to Symbolic Regression Using Feyn". arXiv: 2104.05417 [cs.LG].
- 1 2 3 Abzu (2022-07-22). "What is a QLattice?".
- 1 2 Wenninger, Simon; Kaymakci, Can; Wiethe, Christian (2022). "Explainable long-term building energy consumption prediction using QLattice". Applied Energy. Elsevier BV. 308: 118300. doi:10.1016/j.apenergy.2021.118300. ISSN 0306-2619. S2CID 245428233.
- 1 2 Wilstrup, Casper; Hedley, Paula L.; Rode, Line; Placing, Sophie; Wøjdemann, Karen R.; Shalmi, Anne-Cathrine; Sundberg, Karin; Christiansen, Michael (2022-06-30), Symbolic regression analysis of interactions between first trimester maternal serum adipokines in pregnancies which develop pre-eclampsia, Cold Spring Harbor Laboratory, doi:10.1101/2022.06.29.22277072, S2CID 250331945
- ↑ Michael Kommenda; William La Cava; Maimuna Majumder; Fabricio Olivetti de França; Marco Virgolin (2022-07-22). "SRBench Competition 2022: Interpretable Symbolic Regression for Data Science".
- 1 2 Bharadi, Vinayak (2021-07-30). "QLattice Environment and Feyn QGraph Models—A New Perspective Toward Deep Learning". Emerging Technologies for Healthcare. Wiley. pp. 69–92. doi:10.1002/9781119792345.ch3. ISBN 9781119792345. S2CID 238793347.
- ↑ Riyantoko, Prismahardi Aji; Diyasa, I Gede Susrama Mas (2021-10-28). "F.Q.A.M" Feyn-QLattice Automation Modelling: Python Module of Machine Learning for Data Classification in Water Potability. IEEE. pp. 135–141. doi:10.1109/icimcis53775.2021.9699371. ISBN 978-1-6654-2733-3.
- ↑ Wilstup, Casper; Cave, Chris (2021-01-15), Combining symbolic regression with the Cox proportional hazards model improves prediction of heart failure deaths, Cold Spring Harbor Laboratory, doi:10.1101/2021.01.15.21249874, S2CID 231609904
- 1 2 3 Christensen, Niels Johan; Demharter, Samuel; Machado, Meera; Pedersen, Lykke; Salvatore, Marco; Stentoft-Hansen, Valdemar; Iglesias, Miquel Triana (2022-06-22). "Identifying interactions in omics data for clinical biomarker discovery using symbolic regression". Bioinformatics. Oxford University Press (OUP). 38 (15): 3749–3758. doi:10.1093/bioinformatics/btac405. ISSN 1367-4803. PMC 9344843 . PMID 35731214.
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