Comments (3)
I can refactor it to adapt the heterogeneous biomedical network, which I always wanted to do before. PyG 2.0 is a good chance as there are many heterogeneous features can be used for reference, but I need to finish my current work first. I estimate the refactor can kick off as early as mid-October. @haipinglu
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GripNet is for graphs, particular KG. Refactor it into a data integration/multimodal learning pipeline?@pz-white
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@Lyric-19 is working on it.
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Related Issues (20)
- PyTorch 2.0 HOT 1
- [Bug] Error raised by version mismatch between PyTorch and Lightning while running tutorial HOT 2
- [Bug] Error raised rdkit from kale\prepdata\chem_transform.py on windows, python 3.10 (with ubuntu no error)
- [Bug] Error raised by 'np.float' which was a deprecated alias for the builtin 'float'.
- Merging all the cnn modules such as seq_nn.py, attention_cnn.py into one cnn.py module
- Refactor QBin to be one level up from Pykale repo, under the pykale umbrella HOT 2
- [Refactor] Considering the incorporation of the OneHotEncoder from scikit-learn into PyKale HOT 3
- [Refactor] Merge all evaluation metrics into one module HOT 3
- [Feature Request] Consider input parameter validation in PyKale
- [Refactor] Merge modules `losses`, `distance`, and `metrics` to one HOT 8
- Changelog workflow runs failed
- Support to load parameters from a saved checkpoint HOT 1
- Quantile Binning Refactor HOT 7
- [Refactor] Let one config file contain all hyperparameters. HOT 3
- [Bug] Testing data is downloaded into different directory paths
- [Feature Request] Optimizing functional test time with pytest-testmon HOT 1
- Incorrect loss and accuracy found in the digit_dann example
- [Refactor] GitHub actions caching HOT 1
- Module visibility issues
- [Refactor] Modifying add_protonet PR to align with the demo data download separation. HOT 5
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