mims-harvard/scCIPHER

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Created 9 months ago
Updated 9 months ago

mims-harvard/scCIPHER

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scCIPHER: Contextual deep learning on single-cell-enriched knowledge graphs in neurological disorders

TDC

Therapeutics Commons (TDC-2): Multimodal Foundation for Therapeutic Science

Jupyter Notebook

nimfa

Nimfa: Nonnegative matrix factorization in Python

decagon

Graph convolutional neural network for multirelational link prediction

Jupyter Notebook

TFC-pretraining

Self-supervised contrastive learning for time series via time-frequency consistency

UniTS

A unified multi-task time series model.

PrimeKG

Precision Medicine Knowledge Graph (PrimeKG)

Jupyter Notebook

graphml-tutorials

Tutorials for Machine Learning on Graphs

Jupyter Notebook

SubGNN

Subgraph Neural Networks (NeurIPS 2020)

Raindrop

Graph Neural Networks for Irregular Time Series

GraphXAI

GraphXAI: Resource to support the development and evaluation of GNN explainers

scikit-fusion

scikit-fusion: Data fusion via collective latent factor models

G-Meta

Graph meta learning via local subgraphs (NeurIPS 2020)

Raincoat

Domain Adaptation for Time Series Under Feature and Label Shifts

Jupyter Notebook

ohmnet

OhmNet: Representation learning in multi-layer graphs

PINNACLE

Contextualizing protein representations using deep learning on protein networks and single-cell data

TxGNN

TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design

Jupyter Notebook

GNNGuard

Defending graph neural networks against adversarial attacks (NeurIPS 2020)

SHEPHERD

SHEPHERD: Few shot learning for phenotype-driven diagnosis of patients with rare genetic diseases

GNNDelete

General Strategy for Unlearning in Graph Neural Networks

crank

Prioritizing network communities

TimeX

Time series explainability via self-supervised model behavior consistency

SPECTRA

Spectral Framework For AI Model Evaluation

pathways

Disease pathways in the human interactome

fastGNMF

Fast graph-regularized matrix factorization

PDGrapher

Combinatorial prediction of therapeutic perturbations using causally-inspired neural networks

fusenet

Network inference by fusing data from diverse distributions

medusa

Jumping across biomedical contexts using compressive data fusion

life-tree

Evolution of protein interactomes across the tree of life

patient-safety

Population-scale patient safety data reveal inequalities in adverse events before and during COVID-19 pandemic

Jupyter Notebook

nimfa-ipynb

IPython notebooks demonstrating Nimfa's functionality

ngmc

Network-guided matrix completion

BMI702

Biomedical Artificial Intelligence

AWARE

AWARE: Contextualizing protein representations using deep learning on interactomes and single-cell experiments

data-mining-unipv

Short Course on Data Mining at University of Pavia

Jupyter Notebook

collage-dicty

Gene prioritization by compressive data fusion and chaining

copacar

Collective pairwise classification for multi-way (multi-relational) data analysis

mims-harvard.github.io