4 papers
How Much Reconstruction Does Quantum Machine Learning Need? Late Fusion of Independently Trained Quantum Subcircuits
Prabhjot Singh, Adel N. Toosi, Rajkumar Buyya
Circuit cutting lets a large quantum neural network (QNN) run as independent subcircuits on small devices, but rebuilding its outputs by reconstruction carries a classical sampling…
DistributedEstimator: Distributed Training of Quantum Neural Networks via Circuit Cutting
Prabhjot Singh, Adel N. Toosi, Rajkumar Buyya
Circuit cutting decomposes a large quantum circuit into smaller subcircuits executed independently; expectation values are recovered by classically combining subcircuit outcomes. P…
Quantum Federated Learning: Architectural Elements and Future Directions
Siva Sai, Abhishek Sawaika, Prabhjot Singh +1
Federated learning (FL) focuses on collaborative model training without the need to move the private data silos to a central server. Despite its several benefits, the classical FL…
Advanced Real-Time Fraud Detection Using RAG-Based LLMs
Gurjot Singh, Prabhjot Singh, Maninder Singh
Artificial Intelligence has become a double edged sword in modern society being both a boon and a bane. While it empowers individuals it also enables malicious actors to perpetrate…