NVIDIA FLARE has been used in several research studies. In this directory, you can find their reference implementations.
- FedNCA - Equitable Federated Learning with NCA (MICCAI 2025)
- FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language Models (ICML 2024)
- ConDistFL: Conditional Distillation for Federated Learning from Partially Annotated Data (DeCaF 2023)
- FedOBD: Opportunistic Block Dropout for Efficiently Training Large-scale Neural Networks through Federated Learning (IJCAI 2023)
- Fair Federated Medical Image Segmentation via Client Contribution Estimation (CVPR 2023)
- Communication-Efficient Vertical Federated Learning with Limited Overlapping Samples (ICCV 2023)
- Closing the Generalization Gap of Cross-silo Federated Medical Image Segmentation (CVPR 2022)
- Do Gradient Inversion Attacks Make Federated Learning Unsafe? (IEEE Transactions on Medical Imaging 2022)
- Auto-FedRL: Federated Hyperparameter Optimization for Multi-institutional Medical Image Segmentation (ECCV 2022)
- FedBN: Federated Learning on Non-IID Features via Local Batch Normalization (ICLR 2021)
- Privacy-preserving Federated Brain Tumour Segmentation (MLMI 2019)
To provide your own research implementations, please follow this contribution guide.