ccxsun

ccxsun's Stars

• datawhalechina/so-large-lm

  大模型基础: 一文了解大模型基础知识

  2.9k256

• datawhalechina/llm-cookbook

  面向开发者的 LLM 入门教程，吴恩达大模型系列课程中文版

  Language:Jupyter Notebook11.8k1.5k

• gokayfem/awesome-vlm-architectures

  Famous Vision Language Models and Their Architectures

  Language:Markdown38822

• HKUST-LongGroup/Awesome-MLLM-Benchmarks

  564

• EGiunchiglia/C-HMCNN

  Code for paper: "Coherent Hierarchical Multi-Label Classification Networks"

  Language:Python8421

• BradyFU/Awesome-Multimodal-Large-Language-Models

  :sparkles::sparkles:Latest Advances on Multimodal Large Language Models

  12.4k795

• hpcaitech/Open-Sora

  Open-Sora: Democratizing Efficient Video Production for All

  Language:Python22.1k2.2k

• PathologyFoundation/plip

  Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.

  Language:Python27227

• Lightning-AI/torchmetrics

  Machine learning metrics for distributed, scalable PyTorch applications.

  Language:Python2.1k405

• ahxt/g-mixup

  [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification

  Language:Python907

• CheckBoxStudio/BUAAThesis

  北航研究生学位论文模板（Word+LaTeX）.

  Language:TeX537110

• mahmoodlab/MI-Zero

  Visual Language Pretrained Multiple Instance Zero-Shot Transfer for Histopathology Images - CVPR 2023

  Language:Python914

• HobbitLong/SupContrast

  PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)

  Language:Python3.1k529

• openai/CLIP

  CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

  Language:Jupyter Notebook25.7k3.3k

• yanx27/Pointnet_Pointnet2_pytorch

  PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.

  Language:Python3.7k893

• PistonY/torch-toolbox

  🛠 Toolbox to extend PyTorch functionalities

  Language:Python41756

• Tencent/MedicalNet

  Many studies have shown that the performance on deep learning is significantly affected by volume of training data. The MedicalNet project provides a series of 3D-ResNet pre-trained models and relative code.

  Language:Python1.9k414

• datong-new/Point-GNN.pytorch

  Language:Python6311

• jw9730/tokengt

  [NeurIPS'22] Tokenized Graph Transformer (TokenGT), in PyTorch

  Language:Python31645

• Shen-Lab/GraphCL

  [NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang Shen

  Language:Python555103

• chendaichao/GCN-pointcloud-classification

  PointNet and GCNs for pointcloud classification.

  Language:Python245

• maggie0106/Graph-CNN-in-3D-Point-Cloud-Classification

  Code for A GRAPH-CNN FOR 3D POINT CLOUD CLASSIFICATION (ICASSP 2018)

  Language:Python24364

• cleanlab/cleanlab

  The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

  Language:Python9.7k749

• Jiangbo-Shi/SGMF

  A Structure-aware Hierarchical Graph-based Multiple Instance Learning Framework for pT Staging in Histopathological Image (TMI 2023)

  Language:Python81

• hila-chefer/Transformer-Explainability

  [CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.

  Language:Jupyter Notebook1.8k241

• paulhager/MMCL-Tabular-Imaging

  Language:Jupyter Notebook9315

• PetarV-/GAT

  Graph Attention Networks (https://arxiv.org/abs/1710.10903)

  Language:Python3.2k645

• openmedlab/SAM-Med2D

  SAM-Med2D: Bridging the Gap between Natural Image Segmentation and Medical Image Segmentation

  Language:Jupyter Notebook612

• bowang-lab/MedSAM

  Segment Anything in Medical Images

  Language:Jupyter Notebook3k407

• YichiZhang98/SAM4MIS

  SAM & SAM 2 for Medical Image Segmentation: Open-Source Project Summary

  73856