This repository is the official implementation of "eQMARL: Entangled Quantum Multi-Agent Reinforcement Learning for Distributed Cooperation over Quantum Channels", published in the Thirteenth ...
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 ...
Calculations show that injecting randomness into a quantum neural network could help it determine properties of quantum ...
New York and Philadelphia Edge Network Activation Positions Datavault AI to Capture Significant Share of Insurance and ...
Abstract: Quantum federated learning (QFL) is a combination of distributed quantum computing and federated machine learning, integrating the strengths of both to enable privacy-preserving ...
Fully practical quantum computers haven’t arrived yet, but the quantum computing industry is ending the year on an optimistic note. At the Q2B Silicon Valley conference in December, which brings ...
Exchange-traded funds (ETFs) can be a great way of gaining access to a complex industry that holds plenty of long-term potential. Quantum computing is one of the world's most intriguing emerging ...
A team of Australian and international scientists has, for the first time, created a full picture of how errors unfold over time inside a quantum computer—a breakthrough that could help make future ...
There is more than one way to describe a water molecule, especially when communicating with a machine learning (ML) model, says chemist Robert DiStasio. You can feed the algorithm the molecule's ...
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