The differentiable simulation library ΦML (Phi-ML), which is e.g. the basis for projects like PhiFlow, has been accepted in JOSS now! Congratulations Philipp 😀 👍 The full version is available here:

Short summary: ΦML is a math and neural network library designed for science applications. It enables you to quickly evaluate many network architectures on your data sets, perform linear and non-linear optimization, and write differentiable simulations. ΦML is compatible with JaxPyTorchTensorFlow and NumPy and your code can be executed on all of these backends.