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gan    音标拼音: [g'æn]
gin的过去式

gin的过去式

Gan \Gan\, imp. of {Gin}. [See {Gin}, v.]
Began; commenced.
[1913 Webster]

Note: Gan was formerly used with the infinitive to form
compound imperfects, as did is now employed. Gan
regularly denotes the singular; the plural is usually
denoted by gunne or gonne.
[1913 Webster]

This man gan fall (i.e., fell) in great
suspicion. --Chaucer.
[1913 Webster]

The little coines to their play gunne hie (i. e.,
hied). --Chaucer.
[1913 Webster]

Note: Later writers use gan both for singular and plural.
[1913 Webster]

Yet at her speech their rages gan relent.
--Spenser.
[1913 Webster]


Gin \Gin\ (g[i^]n), v. i. [imp. & p. p. {Gan} (g[a^]n), {Gon}
(g[o^]n), or {Gun} (g[u^]n); p. pr. & vb. n. {Ginning}.] [OE.
ginnen, AS. ginnan (in comp.), prob. orig., to open, cut
open, cf. OHG. inginnan to begin, open, cut open, and prob.
akin to AS. g[imac]nan to yawn, and E. yawn. [root]31. See
{Yawn}, v. i., and cf. {Begin}.]
To begin; -- often followed by an infinitive without to; as,
gan tell. See {Gan}. [Obs. or Archaic] "He gan to pray."
--Chaucer.
[1913 Webster]

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英文字典中文字典相关资料:


  • gan · GitHub Topics · GitHub
    GitHub is where people build software More than 150 million people use GitHub to discover, fork, and contribute to over 420 million projects
  • GitHub - tensorflow gan: Tooling for GANs in TensorFlow
    TF-GAN is a lightweight library for training and evaluating Generative Adversarial Networks (GANs) Can be installed with pip using pip install tensorflow-gan, and used with import tensorflow_gan as tfgan Well-tested examples Interactive introduction to TF-GAN in
  • GitHub - eriklindernoren PyTorch-GAN: PyTorch implementations of . . .
    Softmax GAN is a novel variant of Generative Adversarial Network (GAN) The key idea of Softmax GAN is to replace the classification loss in the original GAN with a softmax cross-entropy loss in the sample space of one single batch
  • GitHub - ratschlab RGAN: Recurrent (conditional) generative adversarial . . .
    Idea: Use generative adversarial networks (GANs) to generate real-valued time series, for medical purposes As the title suggests The GAN is R GAN because it uses recurrent neural networks for both encoder and decoder (specifically LSTMs)
  • NVlabs denoising-diffusion-gan - GitHub
    Generative denoising diffusion models typically assume that the denoising distribution can be modeled by a Gaussian distribution This assumption holds only for small denoising steps, which in practice translates to thousands of denoising steps in the synthesis process In our denoising diffusion
  • GitHub - poloclub ganlab: GAN Lab: An Interactive, Visual . . .
    GAN Lab is a novel interactive visualization tool for anyone to learn and experiment with Generative Adversarial Networks (GANs), a popular class of complex deep learning models With GAN Lab, you can interactively train GAN models for 2D data distributions and visualize their inner-workings
  • GitHub - Hzzone DU-GAN: DU-GAN: Generative Adversarial Networks with . . .
    DU-GAN This repository contains the PyTorch implementation of the paper: DU-GAN: Generative Adversarial Networks with Dual-Domain U-Net Based Discriminators for Low-Dose CT Denoising accepted by IEEE Transactions on Instrumentation Measurement 2021
  • generative-adversarial-network · GitHub Topics · GitHub
    Generative adversarial networks (GAN) are a class of generative machine learning frameworks A GAN consists of two competing neural networks, often termed the Discriminator network and the Generator network
  • GAN生成对抗网络D_loss和G_loss到底应该怎样变化？ - 知乎
    做 GAN 有一段时间了，可以回答下这个问题。 G是你的任务核心，最后推理用的也是G，所以G的LOSS是要下降收敛接近0的，G的目标是要欺骗到D。 而成功的训练中，由于要达到G欺骗D的目的，所以D的Loss是不会收敛的，在G欺骗D的情况下，D的LOSS会在0 5左右。





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