Wasserstein Transfer Learning.

Toward Fair Federated Learning under Demographic Disparities and Data Imbalance.

Representation Learning to Advance Multi-institutional Studies with Electronic Health Record Data.

DOME: Directional medical embedding vectors from Electronic Health Records.

ARCH: Large-scale knowledge graph via aggregated narrative codified health records analysis.

Contrastive Learning on Multimodal Analysis of Electronic Health Records.

Multimodal representation learning for predicting molecule-disease relations.

Multi-source Learning via Completion of Block-wise Overlapping Noisy Matrices.

Hierarchical Pretraining for Biomedical Term Embeddings.

Multiview Incomplete Knowledge Graph Integration with application to cross-institutional EHR data harmonization.

Consensus Knowledge Graph Learning via Multi-view Sparse Low Rank Block Model.

Federated Offline Reinforcement Learning.

Clinical knowledge extraction via sparse embedding regression (KESER) with multi-center large scale electronic health record data.

BELT: Blockwise Missing Embedding Learning Transfomer.

sureLDA: A multidisease automated phenotyping method for the electronic health record.