452 citations · 517 across the 6 of their papers we have counts for
6 papers
Privacy-Preserving Federated Fraud Detection in Payment Transactions with NVIDIA FLARE
Holger R. Roth, Sarthak Tickoo, Mayank Kumar +18
Fraud-related financial losses continue to rise, while regulatory, privacy, and data-sovereignty constraints increasingly limit the feasibility of centralized fraud detection syste…
C-FedRAG: A Confidential Federated Retrieval-Augmented Generation System
Parker Addison, Minh-Tuan H. Nguyen, Tomislav Medan +13
Organizations seeking to utilize Large Language Models (LLMs) for knowledge querying and analysis often encounter challenges in maintaining an LLM fine-tuned on targeted, up-to-dat…
Supercharging Federated Learning with Flower and NVIDIA FLARE
Holger R. Roth, Daniel J. Beutel, Yan Cheng +13
Several open-source systems, such as Flower and NVIDIA FLARE, have been developed in recent years while focusing on different aspects of federated learning (FL). Flower is dedicate…
Empowering Federated Learning for Massive Models with NVIDIA FLARE
Holger R. Roth, Ziyue Xu, Yuan-Ting Hsieh +12
In the ever-evolving landscape of artificial intelligence (AI) and large language models (LLMs), handling and leveraging data effectively has become a critical challenge. Most stat…
MONAI: An open-source framework for deep learning in healthcare
M. Jorge Cardoso, Wenqi Li, Richard Brown +53
Artificial Intelligence (AI) is having a tremendous impact across most areas of science. Applications of AI in healthcare have the potential to improve our ability to detect, diagn…
NVIDIA FLARE: Federated Learning from Simulation to Real-World
Holger R. Roth, Yan Cheng, Yuhong Wen +20
Federated learning (FL) enables building robust and generalizable AI models by leveraging diverse datasets from multiple collaborators without centralizing the data. We created NVI…