This repository will contain the major papers, books and blog posts on QML
- Combarro & González-Castillo, 2023, A Practical Guide to Quantum Machine Learning and Quantum Optimization, Packt Publishing
- Hidary, 2022, Quantum Computing: An Applied Approach, 2nd edition
- Schuld & Petruccione, 2022, Machine Learning with Quantum Computers
- Wong, 2022. Introduction to classical and quantum computing
- Pattanyak, 2021, Quantum Machine Learning with PythonGitHub
- Ganguly, 2021, Quantum Machine Learning: An Applied Approach
- Zickert, 2021, Hands-On Quantum Machine Learning, Vol-1
- De Maio et al., 2024, Training Computer Scientists for the Challenges of Hybrid Quantum-Classical Computing
- Greinert et al., 2024, Advancing quantum technology workforce: industry insights into qualification and training needs
- Mjeda & Murray, 2024, Quantum Computing Education for Computer Science Students: Bridging the Gap with Layered Learning and Intuitive Analogies
- Meyer et al., 2024, Qiskit-Torch-Module: Fast Prototyping of Quantum Neural Networks
- Rönkkö et al., 2024, On-Premises Superconducting Quantum Computer for Education and Research
- Rosenberg & Holincheck & Colandene, 2024, Science, Technology, Engineering, and Mathematics Undergraduates’ Knowledge and Interest in Quantum Careers: Barriers and Opportunities to Building a Diverse Quantum Workforce
- Dündar-Coecke et al., 2023, Quantum Picturalism: Learning Quantum Theory in High School
- Freericks & Doughty, 2023, Should we trade off higher-level mathematics for abstraction to improve student understanding of quantum mechanics?
- Goorney et al., 2023, The Quantum Curriculum Transformation Framework for the development of Quantum Information Science and Technology Education
- De Luca & Chen, 2023, Teaching Quantum Machine Learning in Computer Science
- Melnikov et al., 2023, Quantum Machine Learning: from physics to software engineering
- Kaur & Venegas-Gomez, 2022, Defining the quantum workforce landscape: a review of global quantum education initiatives
- Mykhailova, 2022, Developing Programming Assignments for Teaching Quantum Computing and Quantum Programming
- Peron et al., 2022, Quantum Undergraduate Education and Scientific Training
- Asfaw et al., 2022, Building a Quantum Engineering Undergraduate Program
- Dzurak et al., 2021, Development of an Undergraduate Quantum Engineering Degree
- Ozhigov 2021, Quantum computations (course of lectures)
- Siddhu & Tayur, 2021, Five Starter Pieces: Quantum Information Science via Semi-definite Programs
- Tang et al., 2021, Teaching quantum information technologies and a practical module for online and offline undergraduate students
- Baker, 2023, Quantum detection of time series anomalies
- Draškić, 2023, How to run big quantum circuits on small quantum computers in PennyLane
- East, 2022, Introduction to Geometric Quantum Machine Learning
- Schuld 2022, Why measuring performance is our biggest blind spot in quantum machine learning
- IEEE Spectrum, 2022, Quantum Error Correction
- Qiskit medium, 2022, We are releasing a free hands-on quantum machine learning course online
- Schuetz & Brubaker & Katzgraber, 2022, Combinatorial Optimization with Physics-Inspired Graph Neural Networks, Amazon Braket
- Albornoz, 2021, How to QML, Pennylane
- Ceroni, 2021, The Quantum Graph Recurrent Neural Network, Pennylane
- Derks et al., 2021, Training and evaluating quantum kernels
- Google AI Blog, 2021, Quantum Machine Learning and the Power of Data
- Dunjko et al., 2020, A non-review of Quantum Machine Learning: trends and explorations
- Qunasys, Accelerating variational quantum algorithms
- What is quantum CNN?
- IBM quantum research, At what cost can we simulate large quantum circuit on small quantum computers
- 2023 Mathematical Aspects of Quantum Learning Workshop, IPAM
- Quantum Google AI, 2022, Quantum Summer Symposium
- QPL 2022, Quantum Physics and Logic
- QTML 2021
- Ijaz, An introduction to Quantum Machine Learning
- Schuld, 2020, Quantum Machine Learning
- Schuld, 2020, QUantum Machine Learning and Pennylane
- Wittek, 2015, What Can We Expect from Quantum Machine Learning?
- Preskill, 2022, PH219, Quantum Computing
- Peter Wittek, 2019, QML
- Qiskit, 2022, Quantum simulation
- Qiskit, 2021, Quantum Machine Learning
- Qiskit, 2020, Quantum computing and Quantum Hardware
- Pennylane, QML
- Xanadu, Codebook
- CERN, Elias Fernandez-Combarro Alvarez, "A practical introduction to quantum computing: from qubits to quantum machine learning and beyond" 7 lectures
- Llyod, 2016, Quantum Machine Learning
- Qiskit
- Pennylane
- Lambeq
- Forest
- Tensorflow-quantum
- Braket
- Cirq
- Ocean
- Strawberry Fields
- Q#
- OpenQAOA
- sQUlearn, Kremlin et al., 2023, A Python Library for Quantum Machine Learning
- Qadence, PasqalQadence paper
- Wu et al., 2024, The Cytnx Library for Tensor Networks
- JuliVQC: an Efficient Variational Quantum Circuit Simulator for Near-Term Quantum Algorithms, Liao et al., 2024