chzh32

chzh32's Stars

• tensorflow/tensorflow

  An Open Source Machine Learning Framework for Everyone

  Language:C++187k7.6k40.2k74.4k

• krishnakumarsekar/awesome-quantum-machine-learning

  Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web

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• Qiskit/qiskit-tutorials

  A collection of Jupyter notebooks showing how to use the Qiskit SDK

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• qiskit-community/qiskit-textbook

  [ARCHIVED] A university quantum algorithms/computation course supplement based on Qiskit

  Language:Jupyter Notebook950450735

• oneTaken/awesome_deep_learning_interpretability

  深度学习近年来关于神经网络模型解释性的相关高引用/顶会论文(附带代码)

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• qiskit-community/qiskit-machine-learning

  Quantum Machine Learning

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• Qiskit/qiskit-aer

  Aer is a high performance simulator for quantum circuits that includes noise models

  Language:C++50633868364

• qiskit-community/ibm-quantum-challenge-2024

  For IBM Quantum Challenge 2024 (5-14 June 2024)

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• qigitphannover/DeepQuantumNeuralNetworks

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• LWKJJONAK/Quantum_Neural_Network_Classifiers

  Codes for efficiently implementing quantum neural network classifiers

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• amyami187/effective_dimension

  The power of quantum neural networks

  Language:Python484017

• GroenteLepel/qiskit-quantum-knn

  A pure quantum knn classifier for a gated quantum computer.

  Language:Python22248

• matteoacrossi/ibmq_open_quantum_systems

  Code for reproducing the results of "IBM Q Experience as a versatile experimental testbed for simulating open quantum systems"

  Language:Jupyter Notebook19207

• matteoacrossi/oqs-jupyterbook

  Course on Open Quantum Systems with Qiskit

  Language:Jupyter Notebook15208

• areeq-hasan/qtransformer

  qTransformer is a quantum circuit neural network classifier based on chained quantum attention mechanism layers, residual layers, and feed-forward neural network layers. Attention is computed using a trainable, parameterized general two-body interaction between word embedding statevectors in a sentence system; residual connections are represented using CX-gates; feed-forward neural network layers are represented using custom variational ansatzes such as RealAmplitudes and EfficientSU2.

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• luzd19/ExpDeepQNN

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• LWKJJONAK/Experimental-quantum-adversarial-learning-with-superconducting-qubits

  Language:Jupyter Notebook8101

• matteoacrossi/adapt_ic-povm

  Learning to measure: adaptive informationally complete POVMs for near-term quantum algorithms

  Language:Jupyter Notebook6202

• peixinshen/DeepQuantumNeuralNetworks-Mathematica

  This Mathematica notebook can be used to classically simulate deep quantum neural networks.

  Language:Mathematica6200

• foxwy/QST-NNGMs-FNN

  Ultrafast quantum state tomography with feed-forward neural networks

  Language:Python520

• marcomistretta/Quantum-DQN

  This repository implements a novel approach to the Cart Pole problem by integrating quantum computing principles into the Deep Q Network. Enhance exploration and policy learning for efficient balancing. Dive in and explore the intersection of quantum computing and deep reinforcement learning.

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• FAU-ITP-II/VQE_ansatz_for_the_J1J2-model

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• gismo63/CollisionModel

  Simulating quantum system dynamics using collision models

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• JessicaJohnBritto/QOSF_Cohort6

  Project on studying Open Quantum System Models and simulating them using OQC Lucy Hardware.

  Language:Jupyter Notebook2212

• JonasRigo/Wave-Function-Learning

  This is a small program to test the ability of Feed Forward Neural Networks to approximate a Quantum Many Body Wave Function

  Language:Python2000

• matteoacrossi/non-separability-multipartite-entanglement

  Code and data for the paper "Experimentally accessible non-separability criteria for multipartite entanglement detection"

  Language:Jupyter Notebook230

• matteoacrossi/practical_qc_ibm

  A lecture given on 7/4/2021 for the Quantum Information course at the University of Turku

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• matteoacrossi/Revised_RL_feedback

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• SnackerBit/HOPS

  Python implementation of the Hierarchy of Pure States (HOPS) and Hierarchy of Matrix Product States (HOMPS) for simulating the time evolution of open non-Markovian quantum systems

  Language:Jupyter Notebook12