
A quantum algorithm for training wide and deep classical neural networks
Given the success of deep learning in classical machine learning, quantu...
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Power of data in quantum machine learning
The use of quantum computing for machine learning is among the most exci...
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Learnability and Complexity of Quantum Samples
Given a quantum circuit, a quantum computer can sample the output distri...
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The Snake Optimizer for Learning Quantum Processor Control Parameters
High performance quantum computing requires a calibration system that le...
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TensorFlow Quantum: A Software Framework for Quantum Machine Learning
We introduce TensorFlow Quantum (TFQ), an open source library for the ra...
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Learning NonMarkovian Quantum Noise from MoiréEnhanced Swap Spectroscopy with Deep Evolutionary Algorithm
Twolevelsystem (TLS) defects in amorphous dielectrics are a major sour...
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Learning to learn with quantum neural networks via classical neural networks
Quantum Neural Networks (QNNs) are a promising variational learning para...
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QuantumAssisted Genetic Algorithm
Genetic algorithms, which mimic evolutionary processes to solve optimiza...
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Establishing the Quantum Supremacy Frontier with a 281 Pflop/s Simulation
Noisy IntermediateScale Quantum (NISQ) computers aim to perform computa...
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Universal discriminative quantum neural networks
Quantum mechanics fundamentally forbids deterministic discrimination of ...
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Barren plateaus in quantum neural network training landscapes
Many experimental proposals for noisy intermediate scale quantum devices...
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Hartmut Neven
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