Neural_Net_Arch_Genealogy.dot

digraph "Neural_Net_Arch_Genealogy" {
    rankdir = LR;
    overlap = scale;

    "Neural Net Arch Genealogy" -> "Reinforcement Learning Algorithms";
    "Reinforcement Learning Algorithms" -> "A3C";
    "Reinforcement Learning Algorithms" -> "DARLA";
    "Reinforcement Learning Algorithms" -> "ACTKR";
    "Reinforcement Learning Algorithms" -> "c51";
    "Neural Net Arch Genealogy" -> "CNN";
    "CNN" -> "AlexNet";
    "CNN" -> "VggNet";
    "CNN" -> "GoogLeNet";
    "CNN" -> "ResNet";
    "CNN" -> "DenseNet";
    "CNN" -> "SENet";
    "CNN" -> "Object Detection";
    "Object Detection" -> "R-CNN";
    "Object Detection" -> "Fast R-CNN";
    "Object Detection" -> "Faster R-CNN";
    "Object Detection" -> "Mask R-CNN";
    "Object Detection" -> "YOLO";
    "Object Detection" -> "SSD";
    "Object Detection" -> "R-FCN";
    "CNN" -> "Semantic Segmentation";
    "Semantic Segmentation" -> "FCN";
    "Semantic Segmentation" -> "DeconvNet";
    "Semantic Segmentation" -> "DeepLab";
    "Semantic Segmentation" -> "U-Net";
    "CNN" -> "Super-resolution";
    "Super-resolution" -> "MemNet";
    "Super-resolution" -> "FSRCNN";
    "Super-resolution" -> "SRCNN";
    "Super-resolution" -> "VDSR";
    "Super-resolution" -> "DRCN";
    "Super-resolution" -> "LabSRN";
    "Super-resolution" -> "EDSR";
    "CNN" -> "TTS";
    "TTS" -> "Wavenet";
    "Neural Net Arch Genealogy" -> "Generative Models";
    "Generative Models" -> "Autoregressive models";
    "Autoregressive models" -> "MADE";
    "Autoregressive models" -> "PixelRNN";
    "Autoregressive models" -> "NADE";
    "Autoregressive models" -> "PixelCNN";
    "Autoregressive models" -> "PixelCNN";
    "Generative Models" -> "Latent variable models";
    "Latent variable models" -> "VAE";
    "VAE" -> "CVAE";
    "VAE" -> "AAE";
    "VAE" -> "AVB";
    "VAE" -> "VQ-VAE";
    "Latent variable models" -> "GAN";
    "GAN" -> "Variants";
    "Variants" -> "CGAN";
    "Variants" -> "DCGAN";
    "Variants" -> "infoGAN";
    "Variants" -> "EBGAN";
    "Variants" -> "ACGAN";
    "Variants" -> "WGAN";
    "Variants" -> "BEGAN";
    "Variants" -> "WGAN-GP";
    "Variants" -> "TripleGAN";
    "GAN" -> "Applications";
    "Applications" -> "Pix2Pix";
    "Applications" -> "PPGN";
    "Applications" -> "StackGAN";
    "Neural Net Arch Genealogy" -> "RNN";
    "RNN" -> "LSTM";
    "RNN" -> "GRU";
    "RNN" -> "ACT";
    "RNN" -> "S2S";
    "S2S" -> "Attention";
    "Attention" -> "Effective Approaches to Attention";
    "Attention" -> "DCN";
    "Attention" -> "Transformer";
    "Neural Net Arch Genealogy" -> "Capsule Net";
    "Neural Net Arch Genealogy" -> "Memory Networks";
    "Memory Networks" -> "Neural Programming";
    "Neural Programming" -> "Neural Turing Machine";
    "Neural Programming" -> "Neural Random-Access Machines";
    "Neural Programming" -> "Hierarchical Attentive Memory";
    "Neural Programming" -> "Neural GPUs Learn Algorithms";
    "Neural Programming" -> "Neural Programmer";
    "Neural Programming" -> "Neural Module Networks";
    "Neural Programming" -> "Hybrid Computing";
    "Memory Networks" -> "Memory Networks";
    "Memory Networks" -> "End-to-End Memory Network";
    "Memory Networks" -> "DMN";
}