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Student
- ShangHai
- https://www.yuque.com/phil
Lists (29)
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Development Tools/Utils/Kits
工具库,坚决不能重复造轮子; [C++ utils] [Python utils] [Go utils] [Java utils] ......🔮 Future ideas
Infer&Training Utils
1. KV Cache FlashAttention等具体的落地方案 2. 模型Finetune框架LLM Applicaton
LLM-EEG
Medical-Dataset
1. 医学图像数据集(放射-超声-病理) 2. 多模态医学数据集(图文 视频) 3. 医学报告Medical-Image-Classification
总结现有的医学图像分类算法Medical-Image-Inverse-Problem
收集整理医学图像反问题求解方面的工作Medical-Image-Segmentation
总结医学图像分割算法MedicalVLM
MLsys-DB-Infra
1. AI 训练及推理框架 Pytorch, MNN(alibaba) 2. 服务端部署推理 Triton 3. AI编译器 TVM TensorRT CuDNN 4. 分布式框架,尤其是在AI领域分布式训练 DeepSpeed vLLM LLaMA-Factory 5. KV cache FlashMultiModel LLM
1. 新模型 2.新角度 3. 新应用PaperList & Research
各平台收集来的论文总结pipeline
Point Cloud Completion
Proj_TODO
S级-基座大模型
文本、多模态基座大模型,收录各大厂的模型;TDA
Tooth AI
Transformer
VisualGrounding
医学图像处理的工具库
方便快速开发医学图像的项目奇奇怪怪的小玩意
开发
扩散模型
毕业论文
细分领域强基框架
编译与高性能计算
侧重底层硬件及算法研究,包括算子、框架等 1. AI底层框架 2. 数据库 3.大数据技术长尾分类
- All languages
- Assembly
- Batchfile
- C
- C#
- C++
- CMake
- CSS
- Clojure
- Cuda
- Dart
- Dockerfile
- Fortran
- FreeMarker
- Go
- HTML
- Java
- JavaScript
- Jsonnet
- Julia
- Jupyter Notebook
- Kotlin
- LLVM
- Lua
- MATLAB
- MDX
- MLIR
- Makefile
- Markdown
- Mermaid
- OCaml
- OpenEdge ABL
- PHP
- PLpgSQL
- Processing
- Python
- QMake
- R
- Ruby
- Rust
- SCSS
- Scala
- Shell
- Stata
- Stylus
- Swift
- SystemVerilog
- TeX
- TypeScript
- Vue
- XSLT
Starred repositories
PyNoetic: A Modular Python Framework for No-Code Development of EEG Brain-Computer Interfaces
Deep learning software to decode EEG, ECG or MEG signals
This is an official implementation of "ModernTCN: A Modern Pure Convolution Structure for General Time Series Analysis" (ICLR 2024 Spotlight), https://openreview.net/forum?id=vpJMJerXHU
[ICLR 2024] M/EEG-based image decoding with contrastive learning. i. Propose a contrastive learning framework to align image and eeg. ii. Resolving brain activity for biological plausibility.
Official code, datasets and checkpoints for "Timer: Generative Pre-trained Transformers Are Large Time Series Models" (ICML 2024) and subsequent works
Official code repository for the paper 'EEGPT: Pretrained Transformer for Universal and Reliable Representation of EEG Signals' [NIPS 2024].
NeurIPS2023 - A generic biosignal learning framework. Large EEG pre-trained models.
Code for the paper "Neuro-GPT: Towards a Foundation Model for EEG"
Codebase for publication "Neural decoding from stereotactic EEG: accounting for electrode variability across subjects" @ NeurIPS (2024)
Code for the paper "On the challenges of detecting MCI using EEG in the wild"
TorchEEG is a library built on PyTorch for EEG signal analysis.
[ICML'25] Pre-training graph contrastive masked autoencoders are strong distillers for EEG
The first EEG foundation model explicitly tailored for the motor imagery (MI) paradigm.
[ICLR 2024 spotlight] Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI
A deep learning framework for physiological data processing and understanding.
ICCV 2025 | ROVI: A 1M-scale dataset with comprehensive image descriptions and open-vocabulary bounding box annotations for instance-grounded text-to-image generation
This is the official GitHub repository of the paper "Dia-LLaMA: Towards Large Language Model-driven CT Report Generation"
Seed1.5-VL, a vision-language foundation model designed to advance general-purpose multimodal understanding and reasoning, achieving state-of-the-art performance on 38 out of 60 public benchmarks.
Pytorch implementation of "LightM-UNet: Mamba Assists in Lightweight UNet for Medical Image Segmentation"
PyTorch implementation of Pointnet2/Pointnet++
Fused Qwen3 MoE layer for faster training, compatible with HF Transformers, LoRA, 4-bit quant, Unsloth
Fully Open Framework for Democratized Multimodal Training
TokLIP: Marry Visual Tokens to CLIP for Multimodal Comprehension and Generation
[NeurIPS 2025] The official PyTorch implementation of the "Vision Function Layer in MLLM".
[EMNLP'24] Code and data for paper "Med-MoE: Mixture of Domain-Specific Experts for Lightweight Medical Vision-Language Models"