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


Most implemented papers

PennyLane: Automatic differentiation of hybrid quantum-classical computations

PennyLaneAI/pennylane 12 Nov 2018

PennyLane's core feature is the ability to compute gradients of variational quantum circuits in a way that is compatible with classical techniques such as backpropagation.

TensorFlow Quantum: A Software Framework for Quantum Machine Learning

tensorflow/quantum 6 Mar 2020

We introduce TensorFlow Quantum (TFQ), an open source library for the rapid prototyping of hybrid quantum-classical models for classical or quantum data.

A divide-and-conquer algorithm for quantum state preparation

qclib/qclib 4 Aug 2020

Results show that we can efficiently load data in quantum devices using a divide-and-conquer strategy to exchange computational time for space.

Quantum Neuron: an elementary building block for machine learning on quantum computers

inJeans/qnn 30 Nov 2017

In the construction of feedforward networks of quantum neurons, we provide numerical evidence that the network not only can learn a function when trained with superposition of inputs and the corresponding output, but that this training suffices to learn the function on all individual inputs separately.

q-means: A quantum algorithm for unsupervised machine learning

JonasLandman/quantum_kmeans_NeurIPS_2019 NeurIPS 2019

For a natural notion of well-clusterable datasets, the running time becomes $\widetilde{O}\left( k^2 d \frac{\eta^{2. 5}}{\delta^3} + k^{2. 5} \frac{\eta^2}{\delta^3} \right)$ per iteration, which is linear in the number of features $d$, and polynomial in the rank $k$, the maximum square norm $\eta$ and the error parameter $\delta$.

Reinforcement Learning with Quantum Variational Circuits

luthierman/quantum-research-colab 15 Aug 2020

This work explores the potential for quantum computing to facilitate reinforcement learning problems.

Experimental Quantum Generative Adversarial Networks for Image Generation

niccolot/QML_ComputerVision 13 Oct 2020

For the first time, we experimentally achieve the learning and generation of real-world hand-written digit images on a superconducting quantum processor.

The power of quantum neural networks

amyami187/effective_dimension 30 Oct 2020

We show that quantum neural networks are able to achieve a significantly better effective dimension than comparable classical neural networks.

Supervised quantum machine learning models are kernel methods

sophchoe/Binary_Classification_Pennylane_Keras 26 Jan 2021

With near-term quantum devices available and the race for fault-tolerant quantum computers in full swing, researchers became interested in the question of what happens if we replace a supervised machine learning model with a quantum circuit.

Practical distributed quantum information processing with LOCCNet

PaddlePaddle/Quantum 28 Jan 2021

Here we introduce LOCCNet, a machine learning framework facilitating protocol design and optimization for distributed quantum information processing tasks.