snap-stanford

snap

Stanford Network Analysis Platform (SNAP) is a general purpose network analysis and graph mining library.

ogb

Benchmark datasets, data loaders, and evaluators for graph machine learning

GraphGym

Platform for designing and evaluating Graph Neural Networks (GNN)

pretrain-gnns

Strategies for Pre-training Graph Neural Networks

deepsnap

Python library assists deep learning on graphs

med-flamingo

neural-subgraph-learning-GNN

stark

Official Code of "STaRK: Benchmarking LLM Retrieval on Textual and Relational Knowledge Bases"

MLAgentBench

GEARS

GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations

relbench

RelBench: Relational Deep Learning Benchmark

roland

comet

[ICLR 2021] Concept Learners for Few-Shot Learning

UCE

UCE is a zero-shot foundation model for single-cell gene expression data

SATURN

prodigy

conformalized-gnn

Uncertainty Quantification over Graph with Conformalized Graph Neural Networks (NeurIPS 2023)

multiscale-interactome

plato

lamp

[ICLR23] First deep learning-based surrogate model that jointly learns the evolution model and optimizes computational cost via remeshing

csr

zeroc

ZeroC is a neuro-symbolic method that trained with elementary visual concepts and relations, can zero-shot recognize and acquire more complex, hierarchical concepts, even across domains

le_pde

LE-PDE accelerates PDEs' forward simulation and inverse optimization via latent global evolution, achieving significant speedup with SOTA accuracy

exposure-segregation

planet

PlaNet: Predicting population response to drugs via clinical knowledge graph

AutoTransfer

caml

ipf-network-inference

tuneup

UCE_decoder