Our team is united by a commitment to advancing scalable, resilient, privacy-preserving federated learning in scientific and edge-computing environments through designing a simulation platform that enables researchers to prototype and validate distributed ML workflows.
Our team is united by a commitment to advancing scalable, resilient, privacy-preserving federated learning in scientific and edge-computing environments through designing a simulation platform that enables researchers to prototype and validate distributed ML workflows.
