Deepxde

DeepXDE supports a new backend PaddlePaddle.🎉🎉🎉

Areas of improvement

- Backend PyTorch supports `dde.nn.PFNN`
- Backend TensorFlow 1.x enables XLA for GPU

This is a bugfix release.

Areas of improvement

- Bug fix: `NeumannBC` and `RobinBC`

Backend JAX supports ODE forward problems.🎉🎉🎉

Areas of improvement

- Backend TensorFlow supports `model.save` and `model.restore`.
- Backend TensorFlow uses `tf.function(jit_compile=True)` for faster speed.

DeepXDE supports physics-informed DeepONet.🎉🎉🎉

Areas of improvement

- Fix the issue when setting random seed via `dde.set_random_seed()`

New APIs

- Support physics-informed DeepONet
- Add function spaces: `dde.data.PowerSeries`, `dde.data.Chebyshev`, `dde.data.GRF`, `dde.data.GRF_KL`, `dde.data.GRF2D`
- Add `dde.data.PDEOperator`
- Add `dde.nn.PIDeepONet`

Areas of improvement

- Fix `is_on_line_segment()` such as `Polygon.boundary_normal()` works for float32
- Refactor backend JAX: utilize `vmap`, and add auxiliary arguments to data.losses

New APIs

- Add `NN.num_trainable_parameters()`

API changes

- `dde.data.MfDataSet` adds a new argument `standardize=False`, which changes the default behavior of `MfDataSet`. In the previous version, "standardize" is used by default.