CHANGELOG

0.2.0

• Add Attention base class, MultiHeadAttention, and ScaledDotProductAttention classes.
• Add branch_network and trunk_network arguments to DeepONet to allow for custom network architectures.
• Add MaskedOperator base class.
• Add DeepCatOperator.
• Restructure documentation, separating notebooks into tutorials and how-to guides.

0.1.0

• Move all content of __init__.py files to sub-modules.
• Add Trainer class to replace operator.fit method.
• Implement BelNet.
• Add Sampler, BoxSampler, UniformBoxSampler, and RegularGridSampler classes.
• Moved DataLoader into the fit method of the Trainer. Therefore, Trainer.fit expects an OperatorDataset now.
• A Criterion now enables stopping the training loop.
• The plotting module has been removed.
• Add timeseries.ipynb example.
• Add Function, FunctionSet, and FunctionOperatorDataset classes.
• Add function.ipynb example.
• Add Benchmark base class.
• Add SineBenchmark.
• Implement DeepNeuralOperator.
• Generalize NeuralOperator to take a list of operators.
• The data.DatasetShapes class becomes operators.OperatorShapes without num_observations attribute.
• Change torch dependency from "==2.1.0" to ">=2.1.0,<3.0.0".
• Change optuna dependency from "3.5.0" to ">=3.5.0,<4.0.0".
• Add FourierLayer and FourierNeuralOperator with example.
• Add benchmarks infrastructure.
• An Operator now takes a device argument.
• Add QuantileScaler class.

0.0.0 (2024-02-22)

• Set up project structure.
• Implement basic functionality.
• Build documentation.
• Create first notebooks.
• Introduce neural operators.
• Add CI/CD.

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Last update: 2024-08-20
Created: 2024-08-20