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conditional-molecular-design-ssvae

dl4chem-geometry

graphvae_approx

Efficient Learning of Non-Autoregressive Graph Variational Autoencoders for Molecular Graph Generation

graphvae_compress

Compressed Graph Representation for Scalable Molecular Graph Generation

image_classification_example

PyTorch Implementation of CNN for Image Classification

kvasir_deep_learning

Medical Image Classification/Segmentation

mol_mpnn

Efficient Learning of Message Passing Neural Networks for Molecular Property Production

molecule_search_nmr

Molecular search by NMR spectrum based on evaluation of matching between spectrum and molecule

nmr_mpnn

Neural Message Passing for NMR Chemical Shift Prediction

nmr_mpnn_pytorch

Neural Message Passing for NMR Chemical Shift Prediction

nmr_weakly_supervised

Predictive Modeling of NMR Chemical Shifts without Using Atomic-level Annotations

reaction_condition_vae

Generative Modeling to Predict Multiple Suitable Conditions for Chemical Reactions

reaction_yield_nn

Uncertainty-aware prediction of chemical reaction yields with graph neural networks

retention_time_gnn

Retention Time Prediction through Learning from Small Training Dataset with Pre-Trained Graph Neural Network