- Quantum Reinforcement Learning
- Quantum Boltzmann Machine
- Quantum Perceptron Models
- Quantum Machine Learning
- Quantum gradient descent and Newton's method for constrained polynomial optimization
- Reinforcement Learning Using Quantum Boltzmann Machines
- A Survey of Quantum Learning Theory
- Quantum machine learning: a classical perspective
- Opportunities and challenges for quantum-assisted machine learning in near-term quantum computers
- Quantum autoencoders via quantum adders with genetic algorithms
- Multiqubit and multilevel quantum reinforcement learning with quantum technologies
- Quantum Hopfield neural network
- Automated optimization of large quantum circuits with continuous parameters
- Quantum Neuron: an elementary building block for machine learning on quantum computers
- A quantum algorithm to train neural networks using low-depth circuits
- Unitary quantum perceptron as efficient universal approximator
- A generative modeling approach for benchmarking and training shallow quantum circuits
- Quantum Variational Autoencoder
- Classification with Quantum Neural Networks on Near Term Processors
- Quantum machine learning in feature Hilbert spaces
- Barren plateaus in quantum neural network training landscapes
- Towards Quantum Machine Learning with Tensor Networks
- Circuit-centric quantum classifiers
- Hierarchical quantum classifiers
- Quantum generative adversarial networks
- Quantum generative adversarial learning
- Quantum machine learning for data scientists
- Supervised learning with quantum enhanced feature spaces
- Universal discriminative quantum neural networks
- Continuous-variable quantum neural networks
- A Universal Training Algorithm for Quantum Deep Learning
- Bayesian Deep Learning on a Quantum Computer
- A quantum-inspired classical algorithm for recommendation systems
- Quantum generative adversarial learning in a superconducting quantum circuit
- Quantum algorithms and lower bounds for convex optimization
- Production of photonic universal quantum gates enhanced by machine learning
- Quantum Convolutional Neural Networks
- The Expressive Power of Parameterized Quantum Circuits
- Quantum-inspired classical algorithms for principal component analysis and supervised clustering
- An Artificial Neuron Implemented on an Actual Quantum Processor
- Quantum-inspired low-rank stochastic regression with logarithmic dependence on the dimension
- Graph Cut Segmentation Methods Revisited with a Quantum Algorithm
- q-means: A quantum algorithm for unsupervised machine learning
- Quantum Statistical Inference
- Quantum Sparse Support Vector Machines
- Efficient Learning for Deep Quantum Neural Networks
- Quantum hardness of learning shallow classical circuits
- Sublinear quantum algorithms for training linear and kernel-based classifiers
- Building quantum neural networks based on swap test
- Parameterized quantum circuits as machine learning models
- Machine Learning Phase Transitions with a Quantum Processor
- Sampling-based sublinear low-rank matrix arithmetic framework for dequantizing quantum machine learning
- Quantum Algorithms for Deep Convolutional Neural Networks
- Hybrid Quantum-Classical Convolutional Neural Networks
- Machine learning method for state preparation and gate synthesis on photonic quantum computers
- Quantum Machine Learning: What Quantum Computing Means to Data Mining
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