• webinars-new

  Webinars Federated Learning (FL) is a machine learning approach that allows a model to be trained across multiple decentralised devices or servers holding local data samples, without exchanging them.

• Federation of Agents

  Federation of Agents A semantics-aware fabric for coordinating large, heterogeneous AI agents. This paper introduces Federation of Agents (FoA), a…

• Federated Anaytics

  Federated Anaytics CAFEIN extends beyond training with federated analytics capabilities, enabling distributed statistical analysis across sensitive datasets.

• Federated Evaluation

  Federated Evaluation The machine learning lifecycle requires rigorous validation. CAFEIN provides federated evaluation tools that allow models to…

• Edge Devices for personalized and privacy preserving patient care

  Edge Devices for personalized and privacy preserving patient care The medical field is shifting from generic approaches to personalized, data-driven, risk-based care.

• Secure Aggregation

  Secure Aggregation This project enhances the CAFEIN® platform by integrating secure aggregation capabilities into federated learning (FL) and federated analytics.

• CO2 tracker

  CAFEIN® CO₂ Tracker & Optimiser  Artificial Intelligence and big-data analytics are transforming industries, but they also bring a hidden cost to our planet.

• caso

  CASO The CERN accelerator complex is a safety-critical, interconnected system-of-systems where reliability is paramount. Traditional model-based maintenance struggles with evolving system behavior and rapidly growing, heterogeneous sensor data.

• Stella

  STELLA The project integrates the CAFEIN® federated learning (FL) platform with the STELLA …

• MIP

  Federated Intelligence for Robust and Transparent Market Visibility of the Supply Chain in Global Health Crises Global health supply chains are complex systems spanning raw materials, manufacturing, logistics, and last-mile delivery.

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