Privacy-Preserving Federated Learning over Vertically and Horizontally Partitioned Data for Financial Anomaly Detection

no code implementations • 30 Oct 2023 • Swanand Ravindra Kadhe, Heiko Ludwig, Nathalie Baracaldo, Alan King, Yi Zhou, Keith Houck, Ambrish Rawat, Mark Purcell, Naoise Holohan, Mikio Takeuchi, Ryo Kawahara, Nir Drucker, Hayim Shaul, Eyal Kushnir, Omri Soceanu

The effective detection of evidence of financial anomalies requires collaboration among multiple entities who own a diverse set of data, such as a payment network system (PNS) and its partner banks.

Anomaly Detection Federated Learning +1

Accelerating Physics-Based Simulations Using Neural Network Proxies: An Application in Oil Reservoir Modeling

no code implementations • 23 May 2019 • Jiri Navratil, Alan King, Jesus Rios, Georgios Kollias, Ruben Torrado, Andres Codas

We develop a proxy model based on deep learning methods to accelerate the simulations of oil reservoirs--by three orders of magnitude--compared to industry-strength physics-based PDE solvers.