Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond

Towards Efficient Shapley Value Estimation via Cross-contribution Maximization

Repository of SauronUNet paper

DCFP: Distribution Calibrated Filter Pruning for Lightweight and Accurate Long-tail Semantic Segmentation

Salinity and turbidity detection of water ponds using Satellite imagery

The first realistic and public dataset with rare undesirable real events in oil wells.

Deep learning tools for predicting oil well data

FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs o…

This is the code repository for the following paper: "Model pruning enables efficient federated learning on edge devices".

Federated Dynamic Sparse Training

Awasome Papers and Resources in Deep Neural Network Pruning with Source Code.

Greedy layer pruning for transformer models.

This project is the official implementation of our accepted IEEE TPAMI paper Diverse Sample Generation: Pushing the Limit of Data-free Quantization

Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)

prune ViT-B/16 through shapley value

Pytorch reimplementation of the Vision Transformer (An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale)

This is a collection of our NAS and Vision Transformer work.

This pytorch package implements PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance (ICML 2022).

Python机器学习算法技术博客，有原创干货！有code实践！ 【更多内容敬请关注公众号 "算法进阶"】

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

东南大学幻灯片模板（豪华版）:clipboard:

[T-PAMI'23] PAGCP for the compression of YOLOv5

PyTorch implementation of UNet++ (Nested U-Net).

SQuant [ICLR22]

[NeurIPS 2023] LLM-Pruner: On the Structural Pruning of Large Language Models. Support Llama-3/3.1, Llama-2, LLaMA, BLOOM, Vicuna, Baichuan, TinyLlama, etc.

In progress.