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- Support ANI datasets.
- Support of Coulomb Matrix with DScribe. This serves as an example to implement all descriptors available in that library.
models.kernelridgepartially improved efficiency of
to_pandas()method to convert features to DataFrame.
- Print date where a module was accessed.
- New base classes that can be used to build new features and model modules.
Annealer()class for training VAEs. Right now it is hardcoded in the VAE class but will be improved later.
- Addition of
StepLRlearning rate schedulers.
- ml4chem.data.visualization: Added kwargs to plot_atomic_features()
- Improved memory usage of Gaussian() at "training", and fixed KernelRidge.
batch_sizekeyword argument can be passed to the
Potentials.load()function so that we can do predictions of trajectory files instead of Atoms().
- Interactive plotting support with addition of
- Improved documentation.
- Addition of a Variational Autoencoder class (VAE), and a
- Renamed module
- Renamed class