Finalized repository for IJCNN submission - #4
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…d visualization and fixed some preprocessing steps
…custom loss function
…to mads-factor
…ct temporal sequences
…riment config, fixed microstructure data loading.
- Removed obsolete configuration files for transformer microstructure and temperature experiments. - Updated evaluation function to disable Weights & Biases logging by default and improved solidification metrics extraction. - Introduced temperature constants for solidification in laser_types.py. - Refined solidification loss computation in loss.py, including dynamic temperature normalization and weight adjustments. - Added new DeepCNN_MLP model architecture for spatiotemporal prediction, including medium and large variants. - Implemented medium variant of PredRNN to match DeepCNN_LSTM_Medium size. - Updated training script to use new temperature constants and adjusted solidification weights. - Enhanced model loading and utility functions to support new model architectures. - Adjusted visualization functions to correct image orientation in plots.
MadSoeDK
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Refactoring of code to ensure reproduceability, well-tested and good structure of code.