This repository is the official implementation of "eQMARL: Entangled Quantum Multi-Agent Reinforcement Learning for Distributed Cooperation over Quantum Channels", published in the Thirteenth ...

Research Assistant at Cleveland State University and Programme Lead at the African Quantum Consortium, Mrs Temitope Adeniyi, ...

Abstract: This study presents a comprehensive survey on Quantum Machine Learning (QML) along with its current status, challenges, and perspectives. QML combines quantum computing and machine learning ...

Overview Explore cutting-edge AI and quantum-ready encryption projects to strengthen skills in defending against modern ...

Imagine a future where quantum computers supercharge machine learning—training models in seconds, extracting insights from massive datasets and powering next-gen AI. That future might be closer than ...

IIT Delhi inaugurates its seventh batch of Certification in Quantum Computing & Machine Learning. This fully online program integrates theoretical insight with real-world application, preparing ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

Quantum computing innovations have garnered significant attention for their potential to revolutionize industries, with the energy sector being one of the most promising areas for application. As ...

Quantum computers may be able to run useful algorithms more quickly, thanks to a new quantum router that helps data get to the right place faster. Traditional computers avoid becoming slow when faced ...

TorchQC is a Python library that is based on the PyTorch deep learning library. Quantum operations and dynamics are entirely implemented using the PyTorch tensor mechanism. This makes all generated ...