Papers with Code 아카이브

Quantum Machine Learning

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/XanaduAI/pennylane-plugin-template

PennyLane: Automatic differentiation of hybrid quantum-classical computations

https://github.com/XanaduAI/pennylane-pq

PennyLane: Automatic differentiation of hybrid quantum-classical computations

https://github.com/XanaduAI/pennylane-qiskit

PennyLane: Automatic differentiation of hybrid quantum-classical computations

https://github.com/XanaduAI/pennylane-qulacs

PennyLane: Automatic differentiation of hybrid quantum-classical computations

https://github.com/XanaduAI/pennylane-sf

PennyLane: Automatic differentiation of hybrid quantum-classical computations

https://github.com/XanaduAI/qml

PennyLane: Automatic differentiation of hybrid quantum-classical computations

https://github.com/adjs/dcsp

A divide-and-conquer algorithm for quantum state preparation

https://github.com/amyami187/effective_dimension

The power of quantum neural networks

https://github.com/andre-juan/good_quantum_kernels

A rigorous and robust quantum speed-up in supervised machine learning

https://github.com/ard-srp/qml_analysis

TensorFlow Quantum: A Software Framework for Quantum Machine Learning

https://github.com/askolik/noisy_qrl

Equivariant quantum circuits for learning on weighted graphs

https://github.com/bagmk/Quantum_Machine_Learning_Express

Evaluation of Parameterized Quantum Circuits: on the relation between classification accuracy, expressibility and entangling capability

https://github.com/bmw-group-quantum/quark

Application-Oriented Benchmarking of Quantum Generative Learning Using QUARK

https://github.com/bsc-quantic/tn4ml/tree/master/docs/source/examples/tnad_latent

Tensor Network for Anomaly Detection in the Latent Space of Proton Collision Events at the LHC

https://github.com/detasar/quantum_computing_notebooks/blob/main/SVC_VS_gridSearchQSVC.ipynb

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

https://github.com/iisharankov/QuantumStateTomography

Variational Quantum Circuits for Quantum State Tomography

https://github.com/inJeans/qnn

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

https://github.com/incud/combinatorial-optimization-quantum-embeddings

Quantum Advantage Seeker with Kernels (QuASK): a software framework to speed up the research in quantum machine learning

https://github.com/javierrd/Avoiding-Loc-Min-in-VQCs-with-NNs

PennyLane: Automatic differentiation of hybrid quantum-classical computations

https://github.com/jonastyw/quantum-rnns

The power of quantum neural networks

https://github.com/luthierman/quantum-research

Reinforcement Learning with Quantum Variational Circuits

https://github.com/luthierman/quantum-research-colab

Reinforcement Learning with Quantum Variational Circuits

https://github.com/matibilkis/qvans

A semi-agnostic ansatz with variable structure for quantum machine learning

https://github.com/michaelkoelle/quantum-diffusion

Quantum Denoising Diffusion Models

https://github.com/niccolot/QML_ComputerVision

Experimental Quantum Generative Adversarial Networks for Image Generation

https://github.com/niccolot/QML_ComputerVision/tree/main/image_generation

Experimental Quantum Generative Adversarial Networks for Image Generation

https://github.com/nkmjm/qiML

A quantum-inspired classical algorithm for recommendation systems

https://github.com/peiyong-addwater/hamembedding

Quantum Hamiltonian Embedding of Images for Data Reuploading Classifiers

https://github.com/prantik-pdeb/Quantum-Machine-Learning

Power of data in quantum machine learning

https://github.com/pwegrzyn/pennylane-extra

PennyLane: Automatic differentiation of hybrid quantum-classical computations

https://github.com/qiskit/qiskit-machine-learning

Qiskit Machine Learning: an open-source library for quantum machine learning tasks at scale on quantum hardware and classical simulators

https://github.com/qsar-ubc/pennylane_more_qutrit_ops

PennyLane: Automatic differentiation of hybrid quantum-classical computations

https://github.com/rickyHong/Pennylane-repl

PennyLane: Automatic differentiation of hybrid quantum-classical computations

https://github.com/sophchoe/Binary_Classification_Pennylane_Keras

Supervised quantum machine learning models are kernel methods

https://github.com/theopensi/qml-qpf

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

https://github.com/vutuanhai237/Encoding_state_combine_with_cswap

A divide-and-conquer algorithm for quantum state preparation

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.