qml-vqa-library
github.com/ericardomuten/qml-vqa-library ↗A curated list of recent textbooks, reviews, perspectives, and research papers related to quantum machine learning, variational quantum algorithms, tensor networks, and classical machine learning applications in quantum systems.
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Textbooks ^Reviews & Perspectives ^Quantum Classifier ^Quantum Convolutional Neural Networks ^Quantum Graph Neural Networks ^Quantum Generative Models & Quantum GANs ^Quantum Boltzmann Machines ^Variational Quantum Eigensolver ^Quantum Optimization ^Quantum Reinforcement Learning ^Quantum Autoencoders ^Training & Circuit Construction Techniques ^Embedding/Encoding Techniques ^Circuit Learning Capability Analysis (Expressivity, Entanglement, etc.) ^Barren Plateaus Analysis ^Gradient Techniques ^Tensor Networks ^Quantum Image Processing ^Classical Machine Learning Applications in Quantum Computing ^Uncategorized (yet) ^
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Variational Quantum Eigensolver ^
- An adaptive variational algorithm for exact molecular simulations on a quantum computer
- Application of Quantum Machine Learning to VLSI Placement
- A variational eigenvalue solver on a photonic quantum processor
- Classically-Boosted Variational Quantum Eigensolver
- Measurement-Based Variational Quantum Eigensolver
- Meta-Variational Quantum Eigensolver: Learning Energy Profiles of Parameterized Hamiltonians for Quantum Simulation
Barren Plateaus Analysis ^
- Analyzing the barren plateau phenomenon in training quantum neural networks with the ZX-calculus
- Barren plateaus in quantum neural network training landscapes
- Cost function dependent barren plateaus in shallow parametrized quantum circuits
- Diagnosing barren plateaus with tools from quantum optimal control
Quantum Generative Models & Quantum GANs ^
- Anomaly detection with variational quantum generative adversarial networks
- Dual-Parameterized Quantum Circuit GAN Model in High Energy Physics
- Experimental Quantum Generative Adversarial Networks for Image Generation
- Generation of High-Resolution Handwritten Digits with an Ion-Trap Quantum Computer
- Near-term quantum-classical associative adversarial networks
- Noise Robustness and Experimental Demonstration of a Quantum Generative Adversarial Network for Continuous Distributions
Reviews & Perspectives ^
- A non-review of Quantum Machine Learning: trends and explorations
- Opportunities and challenges for quantum-assisted machine learning in near-term quantum computers
- Quantum Chemistry in the Age of Quantum Computing
- Quantum Deep Learning Neural Networks
- Quantum machine learning
- Quantum machine learning: a classical perspective
Quantum Classifier ^
- Application of Quantum Machine Learning to High Energy Physics Analysis at LHC using IBM Quantum Computer Simulators and IBM Quantum Computer Hardware
- Application of Quantum Machine Learning using the Quantum Kernel Algorithm on High Energy Physics Analysis at the LHC
- A rigorous and robust quantum speed-up in supervised machine learning
- Circuit-centric quantum classifiers
- Classification with Quantum Neural Networks on Near Term Processors
- Data re-uploading for a universal quantum classifier
Quantum Optimization ^
- A Quantum Approximate Optimization Algorithm
- Improving Variational Quantum Optimization using CVaR
- Quantum approximate optimization of non-planar graph problems on a planar superconducting processor
- Quantum gradient algorithm for general polynomials
- Quantum optimization using variational algorithms on near-term quantum devices
- Qubit-efficient encoding schemes for binary optimisation problems
Quantum Convolutional Neural Networks ^
- A quantum deep convolutional neural network for image recognition
- A Tutorial on Quantum Convolutional Neural Networks (QCNN)
- Decentralizing Feature Extraction with Quantum Convolutional Neural Network for Automatic Speech Recognition
- Explorations in Quantum Neural Networks with Intermediate Measurements
- Hybrid Quantum-Classical Convolutional Neural Networks
- Methods for accelerating geospatial data processing using quantum computers
Quantum Graph Neural Networks ^
- A Quantum Graph Neural Network Approach to Particle Track Reconstruction
- A Tutorial on Quantum Graph Recurrent Neural Network (QGRNN)
- Hybrid Quantum-Classical Graph Convolutional Network
- Particle Track Reconstruction with Quantum Algorithms
- Performance of Particle Tracking Using a Quantum Graph Neural Network
- Quantum Graph Neural Networks
Showing a sample of 119 resources. View the full list on GitHub →