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This is the formal code implementation of the CVPR 2022 paper 'Federated Class Incremental Learning'.
A curated list of references for MLOps
cvpr2024/cvpr2023/cvpr2022/cvpr2021/cvpr2020/cvpr2019/cvpr2018/cvpr2017 论文/代码/解读/直播合集,极市团队整理
Perform data science on data that remains in someone else's server
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 on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at scale.
[CVPR 2022--Oral] Restormer: Efficient Transformer for High-Resolution Image Restoration. SOTA for motion deblurring, image deraining, denoising (Gaussian/real data), and defocus deblurring.
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
Avalanche: an End-to-End Library for Continual Learning based on PyTorch.
Master Federated Learning in 2 Hours—Run It on Your PC!
collection of diffusion model papers categorized by their subareas
An easy-to-use federated learning platform