张涵's repositories
MiniGPT-4
Open-sourced codes for MiniGPT-4 and MiniGPT-v2 (https://minigpt-4.github.io, https://minigpt-v2.github.io/)
LLaVA-Med
Large Language-and-Vision Assistant for BioMedicine, built towards multimodal GPT-4 level capabilities.
LLaVA
[NeurIPS'23 Oral] Visual Instruction Tuning: LLaVA (Large Language-and-Vision Assistant) built towards GPT-4V level capabilities.
llama
Inference code for LLaMA models
Chat2Brain
An Iterative Optimizing Framework for Text2Brain with ChatGPT
BLIP
PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
stable-diffusion
A latent text-to-image diffusion model
dgl
Python package built to ease deep learning on graph, on top of existing DL frameworks.
data-augmentation-review
List of useful data augmentation resources. You will find here some not common techniques, libraries, links to GitHub repos, papers, and others.
StableDiffusionReconstruction
Takagi and Nishimoto, CVPR 2023
dgl-lifesci
Python package for graph neural networks in chemistry and biology
cocoapi
COCO API - Dataset @ http://cocodataset.org/
segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
brain-diffuser
Official repository for the paper "Brain-Diffuser: Natural scene reconstruction from fMRI signals using generative latent diffusion" by Furkan Ozcelik and Rufin VanRullen.
gcn
Implementation of Graph Convolutional Networks in TensorFlow
chatgpt_academic
科研工作专用ChatGPT拓展，特别优化学术Paper润色体验，支持自定义快捷按钮，支持markdown表格显示，Tex公式双显示，代码显示功能完善，新增本地Python工程剖析功能/自我剖析功能
text2brain
Generating brain activation maps from free-form text query
nsd_access
python package to access the data of the NSD (natural scenes dataset) fMRI project
machine-learning
something about machine learning
Mathematical-modeling
参加数学建模时用到的一些东西
Feihualing
a simple app
non-stationary_texture_syn
Code used for texture synthesis using GAN