Emma1239's Stars
lucidrains/egnn-pytorch
Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch
jmkim0309/fewshot-egnn
vgsatorras/egnn
snap-stanford/pretrain-gnns
Strategies for Pre-training Graph Neural Networks
BUPT-GAMMA/MetaDyGNN
kaize0409/awesome-few-shot-gnn
An index of algorithms for few-shot learning/meta-learning on graphs
WxxShirley/Awesome-Graph-Prompt
Awesome Papers About Performing Prompting On Graphs
sheldonresearch/ProG
A Unified Python Library for Graph Prompting
dmlc/xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
JDGalileo/galileo
Galileo library for large scale graph training by JD
Kent0n-Li/Medical-Image-Segmentation
MedSeg: Medical Image Segmentation GUI Toolbox 可视化医学图像分割工具箱
PeterYYZhang/few-shot-self-prompt-SAM
This is the official repo for "Self-Prompting Large Vision Models for Few-Shot Medical Image Segmentation"
AngeLouCN/SAMSNeRF
Segment Anything Model (SAM) Guides Dynamic Surgical Scene Reconstruction by Neural Radiance Field (NeRF)
mazurowski-lab/segment-anything-medical-evaluation
Code for "Segment Anything Model for Medical Image Analysis: an Experimental Study" in Medical Image Analysis
YichiZhang98/SAM4MIS
SAM & SAM 2 for Medical Image Segmentation: Open-Source Project Summary
MedicineToken/Medical-SAM-Adapter
Adapting Segment Anything Model for Medical Image Segmentation
hitachinsk/SAMed
The implementation of the technical report: "Customized Segment Anything Model for Medical Image Segmentation"
Jack47/hack-SysML
The road to hack SysML and become an system expert
TuGraph-family/tugraph-analytics
TuGraph Analytics is a distributed graph compute engine.
pathwaycom/pathway
Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
ray-project/ray
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
jax-ml/jax
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
openxla/xla
A machine learning compiler for GPUs, CPUs, and ML accelerators
pytorch/xla
Enabling PyTorch on XLA Devices (e.g. Google TPU)
jshun/ligra
Ligra: A Lightweight Graph Processing Framework for Shared Memory
Oneflow-Inc/oneflow
OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.
BBuf/tvm_mlir_learn
compiler learning resources collect.
mindspore-ai/models
thu-pacman/TriCache
A User-Transparent Block Cache Enabling High-Performance Out-of-Core Processing with In-Memory Programs
Haley-hkb/DRGN-dataset
The GNN models and the dataset used in the DRGN