4 papers
Federated Causal Representation Learning in State-Space Systems for Decentralized Counterfactual Reasoning
Nazal Mohamed, Ayush Mohanty, Nagi Gebraeel
Networks of interdependent industrial assets (clients) are tightly coupled through physical processes and control inputs, raising a key question: how would the output of one client…
Federated Learning of Nonlinear Temporal Dynamics with Graph Attention-based Cross-Client Interpretability
Ayse Tursucular, Ayush Mohanty, Nazal Mohamed +1
Networks of modern industrial systems are increasingly monitored by distributed sensors, where each system comprises multiple subsystems generating high dimensional time series dat…
Towards Uncertainty-Aware Federated Granger Causal Learning
Ayush Mohanty, Nazal Mohamed, Nagi Gebraeel
Granger causality recovers directed interactions from time-series data, but in many distributed systems, the data are vertically partitioned across clients, with each client observ…
Federated Granger Causality Learning for Interdependent Clients with State Space Representation
Ayush Mohanty, Nazal Mohamed, Paritosh Ramanan +1
Advanced sensors and IoT devices have improved the monitoring and control of complex industrial enterprises. They have also created an interdependent fabric of geographically distr…