JingWu321's Stars
OPTML-Group/UnlearnCanvas
[NeurIPS 2024 D&B Track] UnlearnCanvas: A Stylized Image Dataset to Benchmark Machine Unlearning for Diffusion Models by Yihua Zhang, Chongyu Fan, Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jiancheng Liu, Gaoyuan Zhang, Gaowen Liu, Ramana Kompella, Xiaoming Liu, Sijia Liu
deepdrdoc/DeepDRiD
Automated machine learning can facilitate the early diagnosis and timely treatment of diabetic retinopathy. Following the 1st Diabetic Retinopathy: Segmentation and Grading Challenge held with ISBI in 2018, we would like to promote the progress further through 2nd challenge using a new dataset, Deep Diabetic Retinopathy Image Dataset (DeepDRiD). The challenge is subdivided into three tasks as follows: A. Dual-View Disease Grading: Classification of fundus images according to the severity level of diabetic retinopathy using dual view retinal fundus images. B. Image Quality Estimation: Fundus quality assessment for overall image quality, artifacts, clarity, and field definition. C. Transfer Learning: Explore the generalizability of a Diabetic Retinopathy (DR) grading system. The robust and generalizable models are expected to be developed to solve clinical issues in reality.
rapotekhin/RetinaMNIST_Research
This is simple research of the RetinaMNIST dataset
hpcaitech/Open-Sora
Open-Sora: Democratizing Efficient Video Production for All
PRIV-Creation/Awesome-Controllable-T2I-Diffusion-Models
A collection of resources on controllable generation with text-to-image diffusion models.
openai/guided-diffusion
ermongroup/ddim
Denoising Diffusion Implicit Models
gmongaras/Diffusion_models_from_scratch
Creating a diffusion model from scratch in PyTorch to learn exactly how they work.
coderpiaobozhe/classifier-free-diffusion-guidance-Pytorch
a simple unofficial implementation of classifier-free diffusion guidance
lucidrains/denoising-diffusion-pytorch
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
unlearning-challenge/starting-kit
Starting kit for the NeurIPS 2023 unlearning challenge
himashi92/Co-BioNet
[Nature Machine Intelligence Journal] Official pytorch implementation for Uncertainty-Guided Dual-Views for Semi-Supervised Volumetric Medical Image Segmentation
adap/flower
Flower: A Friendly Federated AI Framework
CompVis/latent-diffusion
High-Resolution Image Synthesis with Latent Diffusion Models
zoubohao/DenoisingDiffusionProbabilityModel-ddpm-
This may be the simplest implement of DDPM. You can directly run Main.py to train the UNet on CIFAR-10 dataset and see the amazing process of denoising.
FeTS-AI/Challenge
The repo for the FeTS Challenge
dut-media-lab/BOML
Bilevel Optimization Library in Python for Multi-Task and Meta Learning
vis-opt-group/BLO
Bi-level Optimization for Advanced Deep Learning
dk-liang/Awesome-Visual-Transformer
Collect some papers about transformer with vision. Awesome Transformer with Computer Vision (CV)
stratosphereips/awesome-ml-privacy-attacks
An awesome list of papers on privacy attacks against machine learning
eth-sri/bayes-framework-leakage
microsoft/mup
maximal update parametrization (µP)
satwikkansal/wtfpython
What the f*ck Python? 😱
kelseyhightower/nocode
The best way to write secure and reliable applications. Write nothing; deploy nowhere.
innovation-cat/Awesome-Federated-Machine-Learning
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
Princeton-SysML/GradAttack
GradAttack is a Python library for easy evaluation of privacy risks in public gradients in Federated Learning, as well as corresponding mitigation strategies.
JonasGeiping/breaching
Breaching privacy in federated learning scenarios for vision and text
THUYimingLi/backdoor-learning-resources
A list of backdoor learning resources
jjbrophy47/machine_unlearning
Existing Literature about Machine Unlearning
RongKaiWeskerMA/INSTA
The implementation of Learning Instance and Task-Aware Dynamic Kernels for Few Shot Learning