When equipped with quantum processors, their quantum counterparts—called quantum generative adversarial networks (QGANs)—may even exhibit exponential advantages in certain machine learning applications. Here,
Generative Adversarial Networks The generative models considered in this work, GANs,10,11employ two neural networks - a generator and a discriminator - to learn random distributions that are implicitly given by training data samples. Originally, GANs were used in the context of image generation and ...
Generative Adversarial Networks The generative models considered in this work, GANs,10,11employ two neural networks - a generator and a discriminator - to learn random distributions that are implicitly given by training data samples. Originally, GANs were used in the context of image generation and ...
Quantum generative adversarial networks [1804.08641] Quantum generative adversarial networks Benedetti, M., Grant, E., Wossnig, L., & Severini, S. [1806.00463] Adversarial quantum circuit learning for pure state approximation Haozhen Situ, Zhimin He, Lvzhou Li, Shenggen Zheng [1807.01235] Quantum...
量子生成对抗网络(quantum generative adversarial networks, QGAN)是经典GAN的量子版本[2-4].在2018年, Lloyd等[2]提出了3种QGAN的模型, 证明了在比特消耗以及时间复杂度等方面, QGAN比经典GAN具有更好的性能表现. QGAN在金融预测、图像生成以及态制备等应用领域展现出了显著的优势[5-8]. 例如, 在2019年, ...
The proposed method utilizes Block-Batching Domain-Guided Filtering (2B-DGF) for noise reduction and image enhancement, followed by feature extraction using Hamiltonian Quantum Generative Adversarial Networks (HQGANet) to capture complex ulcer patterns. Cell Attention Networks (CANet) are then employed ...
For the description of the quantum generative adversarial learning method, see [378]. A scheme on the classification with gate-model quantum neural networks can be found in [379]. Show moreView article Journal 2019, Computer Science ReviewLaszlo Gyongyosi, Sandor Imre...
(Quantum circuits are the equivalent of runnable code on classical computers.) With the basics of QNNs available, it follows that convolutional neural networks, generative adversarial networks, and others have quantum equivalents. Hidden Markov models, useful in sequence analysis, can also be...
Theqiskit.mlpackage simply contains sample datasets at present.qiskit.aquahas some classification algorithms such as QSVM and VQC (Variational Quantum Classifier), where this data can be used for experiments, and there is also QGAN (Quantum Generative Adversarial Network) algorithm. ...
Moreover the folderDQGANpresents code and resuls from Beer, K., & Müller, G. (2021). Dissipative quantum generative adversarial networks.https://arxiv.org/abs/2112.06088 Releases2 Autoencoders added.Latest Mar 17, 2020 + 1 release