Introduction to Quantum Machine Learning and Quantum Architecture Search
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Abstract (arXiv)
Recent advancements in quantum computing (QC) and machine learning (ML) have fueled significant research efforts aimed at integrating these two transformative technologies. Quantum machine learning (QML), an emerging interdisciplinary field, leverages quantum principles to enhance the performance of ML algorithms. Concurrently, the exploration of systematic and automated approaches for designing high-performance quantum circuit architectures for QML tasks has gained prominence, as these methods empower researchers outside the quantum computing domain to effectively utilize quantum-enhanced tools. This tutorial will provide an in-depth overview of recent breakthroughs in both areas, highlighting their potential to expand the application landscape of QML across diverse fields.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 29 of its 45 references that are in the map. First posted on arXiv 21 Apr 2025.
Builds on
29 of 45 references.
References · 29
- 2020The power of quantum neural networkscited by 379
- 2019Variational Quantum Circuits for Deep Reinforcement Learningcited by 167
- 2020Quantum Long Short-Term Memorycited by 120
- 2021Parametrized quantum policies for reinforcement learningcited by 90
- 2021Federated Quantum Machine Learningcited by 82
- 2020Reinforcement Learning with Quantum Variational Circuitscited by 77
- 2020Quantum Convolutional Neural Networks for High Energy Physics Data Analysiscited by 64
- 2021The Dawn of Quantum Natural Language Processingcited by 61
- 2021Quantum Architecture Search via Deep Reinforcement Learningcited by 60
- 2021Quantum Federated Learning with Quantum Datacited by 53
- 2021An end-to-end trainable hybrid classical-quantum classifiercited by 51
- 2021Variational Quantum Reinforcement Learning via Evolutionary Optimizationcited by 50
17 more
- 2022When BERT Meets Quantum Temporal Convolution Learning for Text Classification in Heterogeneous Computingcited by 40
- 2024Quantum Architecture Search: A Surveycited by 32
- 2021QTN-VQC: An End-to-End Learning framework for Quantum Neural Networkscited by 27
- 2022PQLM -- Multilingual Decentralized Portable Quantum Language Model for Privacy Protectioncited by 26
- 2024Learning to Program Variational Quantum Circuits with Fast Weightscited by 24
- 2023Applying QNLP to sentiment analysis in financecited by 23
- 2021Quantum Architecture Search via Continual Reinforcement Learningcited by 22
- 2023Asynchronous training of quantum reinforcement learningcited by 20
- 2023Efficient quantum recurrent reinforcement learning via quantum reservoir computingcited by 14
- 2024Differentiable Quantum Architecture Search in Asynchronous Quantum Reinforcement Learningcited by 14
- 2023Differentiable Quantum Architecture Search for Quantum Reinforcement Learningcited by 13
- 2024Quantum Machine Learning Architecture Search via Deep Reinforcement Learningcited by 13
- 2024VQC-Based Reinforcement Learning with Data Re-uploading: Performance and Trainabilitycited by 12
- 2024Quantum-Trained Convolutional Neural Network for Deepfake Audio Detectioncited by 12
- 2024Quantum Advantage Actor-Critic for Reinforcement Learningcited by 9
- 2024Reinforcement Learning for Variational Quantum Circuits Designcited by 9
- 2024Evolutionary Optimization for Designing Variational Quantum Circuits with High Model Capacitycited by 9
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Citing papers per year: 2025: 2; 2026: 1.
3 papers.