"See you zoom" is probably the most appropriate way of saying good by at the moment...

#pyPESTO 0.1.0 is out! 🎉😃 Parameter estimation toolbox featuring (esp.): - efficient gradient-based optimization - sampling with PyMC Developers https://bayes.club/@pymc and parallel tempering - profiling - result visualization - integrated with #AMICI and #PEtab ➡️ github.com/icb-dcm/pypesto

Happy to present #pyPESTO a #python package for parameter estimation & uncertainty quantification at this year's #COMBINE2020. You can find the jupyter notebook containing all the code (plus some bonus material) and the slides here: github.com/jvanhoefer/COM…

Interested in #CompBio, #SingleCells or #MathModelling with applications in #metainflammation or #epidemiology? Check out our open PhD and PostDoc positions: nature.com/naturecareers/… nature.com/naturecareers/… Partners: Open Source Economics, ORCHESTRA-Cohort

Well-written piece of code for converting ODE models, comes with docs, CI, tutorials. Totally recommend 👍

Been to one of @cthoyt's amazing introductions to python package design and it really shaped the way I write (scientific) software. I can really recommend them (July 25, 5-8PM CEST), if you want to learn about turning python code to a clean pip-installable python package!

Wir = LightningPose freuen uns wirklich riesig! Vielen Dank und wir sind gespannt, wie sich das Projekt weiter entwickelt!

🎒Summer school: 𝐈𝐧𝐯𝐞𝐫𝐬𝐞 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬 𝐟𝐨𝐫 𝐦𝐮𝐥𝐭𝐢-𝐬𝐜𝐚𝐥𝐞 𝐦𝐨𝐝𝐞𝐥𝐬 💬With: Linda Petzold, Christiane Fuchs, Dennis Prangle , Stefan Engblom, Andreas Hellander ⏰August 22-26 📌@HCM_Bonn ✏️Details+register: hcm.uni-bonn.de/events/eventpa…

Probably one of the most stunning results of our = Jan Hasenauer|s research group: Federated learning has a HUGHE security issue: Data can recovered completely, only using the covariance function, which basically all federated learning frameworks have! biorxiv.org/content/10.110…