Quantum Annealing for Machine Learning Tasks
How quantum annealers are used for machine learning tasks such as training and feature selection, and how they compare with classical methods.
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Quantum Decision Trees and Query Complexity
Quantum decision trees and query complexity: how quantum algorithms evaluate decision trees and how they compare with classical ones.
Quantum Memory Networks and Associative Recall
Quantum memory networks and associative memory models: how quantum states could store and recall patterns, and their current limits.
Quantum Recurrent Neural Networks (QRNN)
Proposals for quantum recurrent neural networks, how they would handle sequences and time series, and the hardware limits today.
Quantum Convolutional Neural Networks (QCNN)
Quantum convolutional neural networks apply convolution and pooling layers to qubits. Their design, uses in classifying quantum states and challenges.
Quantum Autoencoders for Compressing Quantum Data
Quantum autoencoders compress quantum states into fewer qubits using trained circuits. How they work, advantages and current research.
Quantum Linear Regression and Its Data Loading Cost
Quantum algorithms for linear regression promise speedups, but loading the data into quantum states can cancel them. Where they might help.
The Quantum Perceptron: A Neuron Built From Qubits
Proposals for a quantum perceptron built from qubits and gates, how training would work, and how it compares with the classical perceptron.
Quantum GANs: Generative Adversarial Networks on Qubits
Quantum generative adversarial networks pit a quantum generator against a discriminator. Architecture, training and possible applications.
Quantum Reinforcement Learning (QRL) Architectures
Architectures for quantum reinforcement learning, how they compare with classical reinforcement learning, and where they are being tested.
The Variational Quantum Classifier (VQC), Explained
The variational quantum classifier encodes data in a parameterized circuit and trains it with a classical optimizer. Steps, cost function and limits.
Quantum Boltzmann Machines (QBM) for Generative Models
Quantum Boltzmann machines as generative models: how they differ from classical ones, how they are trained and possible uses.