LiamZeng

LiamZeng's Stars

• jaanli/variational-autoencoder

  Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)

  Language:Python1.1k256

• lwneal/counterfactual-open-set

  Counterfactual Image Generation

  Language:Python8223

• rohithreddy024/VAE-GAN-Pytorch

  Generation of 128x128 bird images using VAE-GAN with additional feature matching loss

  Language:Python8423

• seangal/dcgan_vae_pytorch

  dcgan combined with vae in pytorch!

  Language:Python11732

• andersbll/autoencoding_beyond_pixels

  Generative image model with learned similarity measures

  Language:Python43696

• zzzace2000/FIDO-saliency

  Explaining Image Classifiers by Counterfactual Generation

  Language:Jupyter Notebook272

• sigmorphon/2019

  Language:Python1315

• kestory/NJU-GameTheory-Homework

  南京大学 计算机科学与技术系 2018秋季课程 《博弈论及其应用》

  Language:MATLAB5317

• opteroncx/TAN

  Code for paper Triple-Attention Mixed-Link Network for Single-Image Super-Resolution

  Language:Python12

• moskomule/senet.pytorch

  PyTorch implementation of SENet

  Language:Python2.3k440

• MKFMIKU/SrSENet

  An Effective Single-Image Super-Resolution Model Using Squeeze-and-Excitation Networks ICONIP‘18

  Language:Python112

• cs230-stanford/cs230-code-examples

  Code examples in pyTorch and Tensorflow for CS230

  Language:Python3.8k988

• alohaleonardo/Super_Resolution_with_CNNs_and_GANs

  Image Super-Resolution Using SRCNN, DRRN, SRGAN, CGAN in Pytorch

  Language:Jupyter Notebook27276

• RobertGawron/supper-resolution

  Super-resolution (SR) is a method of creating images with higher resolution from a set of low resolution images.

  Language:Python11326

• xinlianghu/svm

  用Python实现SVM多分类器

  Language:Python350100

• aamini/introtodeeplearning

  Lab Materials for MIT 6.S191: Introduction to Deep Learning

  Language:Jupyter Notebook7.2k3.6k