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tdc2website-flask
Publicmims-harvard.github.io
PublicMadrigal
PublicMadrigal: Multimodal AI predicts clinical outcomes of drug combinations from preclinical dataTDC
PublicTherapeutics Commons (TDC-2): Multimodal Foundation for Therapeutic Science- Unified Clinical Vocabulary Embeddings for Advancing Precision Medicine
SPECTRA
PublicSpectral Framework For AI Model EvaluationPDGrapher
PublicCombinatorial prediction of therapeutic perturbations using causally-inspired neural networksUniTS
PublicA unified multi-task time series model.PINNACLE
PublicContextual AI models for single-cell protein biologySHEPHERD
PublicSHEPHERD: Few shot learning for phenotype-driven diagnosis of patients with rare genetic diseasesPrimeKG-2.0
PublicG-Meta
PublicGraph meta learning via local subgraphs (NeurIPS 2020)PrimeKG
PublicPrecision Medicine Knowledge Graph (PrimeKG)GraphXAI
PublicGraphXAI: Resource to support the development and evaluation of GNN explainers- Self-supervised contrastive learning for time series via time-frequency consistency
TxGNN
PublicTxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered designBMI702
PublicscCIPHER
PublicscCIPHER: Contextual deep learning on single-cell-enriched knowledge graphs in neurological disordersTimeX
PublicTime series explainability via self-supervised model behavior consistencyfastGNMF
PublicFast graph-regularized matrix factorizationscikit-fusion
Publicscikit-fusion: Data fusion via collective latent factor modelsGNNGuard
PublicDefending graph neural networks against adversarial attacks (NeurIPS 2020)Raincoat
PublicDomain Adaptation for Time Series Under Feature and Label Shiftsmetapaths
PublicGNNDelete
PublicGeneral Strategy for Unlearning in Graph Neural Networksnimfa-ipynb
Publichydra-zen
Publicdecagon
PublicGraph convolutional neural network for multirelational link predictionRaindrop
PublicGraph Neural Networks for Irregular Time Seriespatient-safety
PublicPopulation-scale patient safety data reveal inequalities in adverse events before and during COVID-19 pandemic