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A Universal Training Algorithm for Quantum Deep Learning
Guillaume Verdon,
Jason Pye
, Michael Broughton
Physics
Research output
:
Working paper
›
Preprint
26
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Dive into the research topics of 'A Universal Training Algorithm for Quantum Deep Learning'. Together they form a unique fingerprint.
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Physics
Phase Error
100%
Deep Learning
100%
Gradients
85%
Networks
71%
Momentum
57%
Optimization
57%
Circuits
42%
Utilization
42%
Neural Network
28%
Heuristics
28%
Quantum Computing
28%
Independent Variables
28%
Learning
28%
Cores
28%
Parameter
28%
Quantum Computer
14%
Information
14%
Adaptation
14%
Simulation
14%
Estimates
14%
Computer Science
Algorithms
100%
Deep Learning
100%
Gradient Descent
71%
Optimization
42%
Networks
42%
Heuristics
28%
Network Parameter
28%
Feedforward Neural Network
14%
Backpropagation Algorithm
14%
Backpropagation
14%
Quantum Circuit
14%
Regularization
14%
Relative Phase
14%
Tunneling
14%
Unification
14%
Parallelization
14%
Deep Neural Network
14%
Optimization Strategy
14%
Quantum Computer
14%
Application
14%
Numerical Simulation
14%
Multiple Application
14%