Search Results for author:
Found 2 papers, 2 papers with code
Neural Networks for Programming Quantum Annealers
We explore a setup for performing classification on labeled classical datasets, consisting of a classical neural network connected to a quantum annealer.
projUNN: efficient method for training deep networks with unitary matrices
In learning with recurrent or very deep feed-forward networks, employing unitary matrices in each layer can be very effective at maintaining long-range stability.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
