KarhouTam

flower

Flower: A Friendly Federated AI Framework

cuda-kernels

Some common CUDA kernel implementations (Not the fastest).

Federated-Averaging-PyTorch

Implementation of FedAvg

FedRecon

PyTorch Implementation of Federated Reconstruction: Partially Local Federated Learning

FL-bench

Benchmark of federated learning. Dedicated to the community. 🤗

KarhouTam

Per-FedAvg

PyTorch Implementation of Personalized federated learning with theoretical guarantees: A model-agnostic meta-learning approach

Personalized-FedAvg

Implementation of Improving Federated Learning Personalization via Model Agnostic Meta Learning

pFedLA

PyTorch implementation of Layer-wised Model Aggregation for Personalized Federated Learning

SCAFFOLD-PyTorch

Implementation of SCAFFOLD: Stochastic Controlled Averaging for Federated Learning

KarhouTam/FL-bench

Benchmark of federated learning. Dedicated to the community. 🤗

KarhouTam/pFedLA

PyTorch implementation of Layer-wised Model Aggregation for Personalized Federated Learning

KarhouTam/SCAFFOLD-PyTorch

Implementation of SCAFFOLD: Stochastic Controlled Averaging for Federated Learning

KarhouTam/Per-FedAvg

PyTorch Implementation of Personalized federated learning with theoretical guarantees: A model-agnostic meta-learning approach

KarhouTam/Federated-Averaging-PyTorch

Implementation of FedAvg

KarhouTam/FedRecon

PyTorch Implementation of Federated Reconstruction: Partially Local Federated Learning

KarhouTam/cuda-kernels

Some common CUDA kernel implementations (Not the fastest).

KarhouTam/Personalized-FedAvg

Implementation of Improving Federated Learning Personalization via Model Agnostic Meta Learning

KarhouTam/KarhouTam

KarhouTam/flower

Flower: A Friendly Federated Learning Framework

KarhouTam/llm.c

LLM training in simple, raw C/CUDA

KarhouTam/ray

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

KarhouTam/karhoutam.github.io