- train.py now identifies if a previous version of the model checkpoints has been saved for both DE and DER
- default.py matches defaults used in experiments
- train.py modified with names of flags made more explicit
- verbosity in data.py and analyze.py
- can load rs DE model in analyze.py
- torch.Tensor error addressed in data.py
- test_data
- test_Analyze --> test_analyze
- Functionality within data.py to set seeds for generate_df for simulate_0D and simulate_2D
- Imports so analyze.py can be imported
- test_Analyze
- Functionality within data.py to set seeds for generate_df for uniform and priors
- Decided to rename src/ to deepuq/ in order for easier imports
- Fixed packaging to enable use of commands for running scripts.
- Updated readme with instructions for downloading and running package
- Initial release of the project with the following features:
- DeepEnsemble: generates or loads data and trains a DE model
- DeepEvidentialRegression: generates or loads data and trains a DER model
- data
- models
- analyze
- train
- This is the first official release of the package.