Differentiable simulation library Phi-ML at JOSS

The differentiable simulation library Φ_ML (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: https://joss.theoj.org/papers/10.21105/joss.06171

Short summary: Φ_ML 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. Φ_ML is compatible with Jax, PyTorch, TensorFlow and NumPy and your code can be executed on all of these backends.