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Tag: graph neural network

Hamiltonian variational ansatz without barren plateaus

Chae-Yeun Park and Nathan KilloranXanadu, Toronto, ON, M5G 2C8, CanadaFind this paper interesting or want to discuss? Scite or leave a comment on SciRate.AbstractVariational...

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Scaling of the quantum approximate optimization algorithm on superconducting qubit based hardware

Johannes Weidenfeller1,2, Lucia C. Valor1, Julien Gacon1,3, Caroline Tornow1,2, Luciano Bello1, Stefan Woerner1, and Daniel J. Egger11IBM Quantum, IBM Research Europe – Zurich2ETH Zurich3Institute...

Busy GPUs: Sampling and pipelining method speeds up deep learning on large graphs

Graphs, a potentially extensive web of nodes connected by edges, can be used to express and interrogate relationships between data, like social connections, financial...

Graph neural network initialisation of quantum approximate optimisation

Nishant Jain1, Brian Coyle2, Elham Kashefi2,3, and Niraj Kumar21Indian Institute of Technology, Roorkee, India.2School of Informatics, University of Edinburgh, EH8 9AB Edinburgh, United Kingdom.3LIP6,...

Developing advanced machine learning systems at Trumid with the Deep Graph Library for Knowledge Embedding

This is a guest post co-written with Mutisya Ndunda from Trumid. Like many industries, the corporate bond...

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