Gumbel-Softmax Variational Autoencoder with Keras. Contribute to EderSantana/gumbel development by creating an account on GitHub.
nlp opencv natural-language-processing deep-learning sentiment-analysis word2vec keras generative-adversarial-network autoencoder glove t-sne segnet keras-models keras-layer latent-dirichlet-allocation denoising-autoencoders svm-classifier resnet-50 anomaly-detection variational-autoencoder Updated Dec 6, ...
F. Chollet et al., Keras, https://github.com/fchollet/keras. M. Abadi et al., TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems, software available from https://www.tensorflow.org/ [arXiv:1603.04467]. I. Loshchilov and F. Hutter, Decoupled Weight Decay Regulariza...
全连接层,Lambda层 from keras.layers import Input, Dense, Lambda from keras.models import Model #引入后端 from keras import backend as K #训练的目标函数 from keras import objectives #数据集MINST from keras.datasets import mnist #定义一些参数 #分批,每次训练100...
Deep neural networks are good at extracting low-dimensional subspaces (latent spaces) that represent the essential features inside a high-dimensional dataset. Deep generative models represented by variational autoencoders (VAEs) can generate and infer hi
I have discussed basics of Autoencoders. We have also set up a simple Autoencoder with the help of the functional Keras interface to Tensorflow 2. This worked flawlessly and we could apply our Autoencoder [AE] to the MNIST dataset. Thus we got a good reference point ...
There are two generative models facing neck to neck in the data generation business right now:Generative Adversarial Nets (GAN)and Variational Autoencoder (VAE). These two models have different take on how the models are trained. GAN is rooted in game theory, its objective is to find the Nas...
2016-Variational Graph Auto-Encoders 介绍了变分图自动编码器(variationalgraphautoencoder,VGAE),它是基于变分自动编码器(variationalauto-encoder,VAE)的无监督学习图结构数据的...在引用网络中的链接预测任务上获得了竞争性结果。 与大多数现有的无监督学习图结构数据和链接预测模型[5、6、7、8]相比,我们的模型可...
encoder network that accepts the original data as input, and returns a vector. This vector is then fed to the second CNN, the decoder that reconstructs the original data. For more information about the architecture you can check out the tutorialImage Compression Using Autoencoders in Keras, ...
We present a variational autoencoder (VAE) applied to cancer gene expression data. A VAE is a deep generative model introduced byKingma and Wellingin 2013. The model has two direct benefits of modeling cancer gene expression data. Automatically engineer non-linear features ...