https://github.com/maniraman-periyasamy/guided-spsa
공식 코드Guided-SPSA: Simultaneous Perturbation Stochastic Approximation assisted by the Parameter Shift Rule
Papers with Code 아카이브
Quantum Machine Learning
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/martaskrt/qdeq
공식 코드https://github.com/mattwright99/thesis
공식 코드Design and Implementation of a Quantum Kernel for Natural Language Processing
https://github.com/mdaamirQ/2-QNSCD
공식 코드https://github.com/mdppml/distributed-secure-kernel-based-qml
공식 코드Distributed and Secure Kernel-Based Quantum Machine Learning
https://github.com/mominul-ssv/alz-cq-cnn
공식 코드https://github.com/mroget/quantum-perceptron-models
공식 코드Quantum Perceptron Revisited: Computational-Statistical Tradeoffs
https://github.com/nicomeyer96/regularized-qpg
공식 코드Robustness and Generalization in Quantum Reinforcement Learning via Lipschitz Regularization
https://github.com/ntuhep-qml/qcgnn
공식 코드Jet Discrimination with Quantum Complete Graph Neural Network
https://github.com/philippaltmann/qcd
공식 코드Challenges for Reinforcement Learning in Quantum Circuit Design
https://github.com/philippaltmann/sequent
공식 코드SEQUENT: Towards Traceable Quantum Machine Learning using Sequential Quantum Enhanced Training
https://github.com/pifparfait/fourier_based_qml
공식 코드https://github.com/positivetechnologylab/Quorum
공식 코드Quorum: Zero-Training Unsupervised Anomaly Detection using Quantum Autoencoders
https://github.com/puyokw/distributedqnns
공식 코드Distributed Quantum Neural Networks via Partitioned Features Encoding
https://github.com/qclib/qclib
공식 코드A divide-and-conquer algorithm for quantum state preparation
https://github.com/qigitphannover/DeepQuantumNeuralNetworks/tree/master/QRNN
공식 코드Learning Quantum Processes with Memory -- Quantum Recurrent Neural Networks
https://github.com/qiskit-community/qiskit-machine-learning
공식 코드https://github.com/qkoopman/QuACK
공식 코드QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning
https://github.com/quantum-jwjae/rl2lqs
공식 코드Reinforcement learning to learn quantum states for Heisenberg scaling accuracy
https://github.com/quantummind/qaml-z
공식 코드https://github.com/quantummind/quantum-deep-neural-network
공식 코드A quantum algorithm for training wide and deep classical neural networks
https://github.com/quark-framework/quark
공식 코드Application-Oriented Benchmarking of Quantum Generative Learning Using QUARK
https://github.com/rezafuru/quantensplit
공식 코드Architectural Vision for Quantum Computing in the Edge-Cloud Continuum
https://github.com/rsln-s/importance-of-kernel-bandwidth-in-quantum-machine-learning
공식 코드https://github.com/sabrinaherbst/hyperparameters_qnn
공식 코드https://github.com/sabrinaherbst/qnn_local_neighborhood
공식 코드https://github.com/sashwatanagolum/elivagar
공식 코드Élivágar: Efficient Quantum Circuit Search for Classification
https://github.com/siheon-park/quic-projects
공식 코드Variational Quantum Approximate Support Vector Machine with Inference Transfer
https://github.com/silverengineered/sliq
공식 코드SLIQ: Quantum Image Similarity Networks on Noisy Quantum Computers
https://github.com/sjerbi/qml-beyond-kernel
공식 코드https://github.com/squlearn/squlearn
공식 코드https://github.com/tensorflow/quantum
공식 코드TensorFlow Quantum: A Software Framework for Quantum Machine Learning
https://github.com/tiago939/QuForge
공식 코드https://github.com/tobias-fllnr/robustnessgeneralizationqml
공식 코드The interplay of robustness and generalization in quantum machine learning
https://github.com/tommasofioravanti/sq-learn
공식 코드https://github.com/trianam/machinelearningmagneticsensing
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.