Quantum Machine Learning

77 papers with code • 2 benchmarks • 1 datasets

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Use these libraries to find Quantum Machine Learning models and implementations


Training robust and generalizable quantum models

daniel-fink-de/training-robust-and-generalizable-quantum-models 20 Nov 2023

We derive tailored, parameter-dependent Lipschitz bounds for quantum models with trainable encoding, showing that the norm of the data encoding has a crucial impact on the robustness against perturbations in the input data.

20 Nov 2023

sQUlearn $\unicode{x2013}$ A Python Library for Quantum Machine Learning

squlearn/squlearn 15 Nov 2023

sQUlearn introduces a user-friendly, NISQ-ready Python library for quantum machine learning (QML), designed for seamless integration with classical machine learning tools like scikit-learn.

15 Nov 2023

Machine Learning in the Quantum Age: Quantum vs. Classical Support Vector Machines

detasar/quantum_computing_notebooks 17 Oct 2023

This work endeavors to juxtapose the efficacy of machine learning algorithms within classical and quantum computational paradigms.

17 Oct 2023

Learning Quantum Processes with Quantum Statistical Queries

chirag-w/qpsq-learning 3 Oct 2023

Learning complex quantum processes is a central challenge in many areas of quantum computing and quantum machine learning, with applications in quantum benchmarking, cryptanalysis, and variational quantum algorithms.

03 Oct 2023

Tensor Ring Optimized Quantum-Enhanced Tensor Neural Networks

konar1987/tr-qnet 2 Oct 2023

Quantum machine learning researchers often rely on incorporating Tensor Networks (TN) into Deep Neural Networks (DNN) and variational optimization.

02 Oct 2023

SLIQ: Quantum Image Similarity Networks on Noisy Quantum Computers

silverengineered/sliq 26 Sep 2023

Exploration into quantum machine learning has grown tremendously in recent years due to the ability of quantum computers to speed up classical programs.

26 Sep 2023

Sub-universal variational circuits for combinatorial optimization problems

lirandepira/paoa-simulations 29 Aug 2023

Quantum variational circuits have gained significant attention due to their applications in the quantum approximate optimization algorithm and quantum machine learning research.

29 Aug 2023

Application of Quantum Pre-Processing Filter for Binary Image Classification with Small Samples

hajimesuzuki999/qpf-bic 28 Aug 2023

Similar to our previous multi-class classification results, the application of QPF improved the binary image classification accuracy using neural network against MNIST, EMNIST, and CIFAR-10 from 98. 9% to 99. 2%, 97. 8% to 98. 3%, and 71. 2% to 76. 1%, respectively, but degraded it against GTSRB from 93. 5% to 92. 0%.

28 Aug 2023

Neural Networks for Programming Quantum Annealers

boschsamuel/nnforprogrammingquantumannealers 13 Aug 2023

We explore a setup for performing classification on labeled classical datasets, consisting of a classical neural network connected to a quantum annealer.

13 Aug 2023

Application-Oriented Benchmarking of Quantum Generative Learning Using QUARK

quark-framework/quark 8 Aug 2023

Benchmarking of quantum machine learning (QML) algorithms is challenging due to the complexity and variability of QML systems, e. g., regarding model ansatzes, data sets, training techniques, and hyper-parameters selection.

08 Aug 2023