10 citations · 11 across the 8 of their papers we have counts for
4 papers · 1 filter
Differentially Private Federated Quantum Learning via Quantum Noise
Atit Pokharel, Ratun Rahman, Shaba Shaon +2
Quantum federated learning (QFL) enables collaborative training of quantum machine learning (QML) models across distributed quantum devices without raw data exchange. However, QFL…
SimQFL: A Quantum Federated Learning Simulator with Real-Time Visualization
Ratun Rahman, Atit Pokharel, Md Raihan Uddin +1
Quantum federated learning (QFL) is an emerging field that has the potential to revolutionize computation by taking advantage of quantum physics concepts in a distributed machine l…
Sporadic Federated Learning Approach in Quantum Environment to Tackle Quantum Noise
Ratun Rahman, Atit Pokharel, Dinh C. Nguyen
Quantum Federated Learning (QFL) is an emerging paradigm that combines quantum computing and federated learning (FL) to enable decentralized model training while maintaining data p…
Quantum Federated Learning for Multimodal Data: A Modality-Agnostic Approach
Atit Pokharel, Ratun Rahman, Thomas Morris +1
Quantum federated learning (QFL) has been recently introduced to enable a distributed privacy-preserving quantum machine learning (QML) model training across quantum processors (cl…