shenzebang

shenzebang's Stars

• eriklindernoren/PyTorch-GAN

  PyTorch implementations of Generative Adversarial Networks.

  Language:Python16.6k2191574.1k

• tkarras/progressive_growing_of_gans

  Progressive Growing of GANs for Improved Quality, Stability, and Variation

  Language:Python6.1k27001.1k

• IDSIA/sacred

  Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.

  Language:Python4.3k70561383

• Newmu/dcgan_code

  Deep Convolutional Generative Adversarial Networks

  Language:Python3.4k15734692

• ajbrock/BigGAN-PyTorch

  The author's officially unofficial PyTorch BigGAN implementation.

  Language:Python2.9k5185480

• igul222/improved_wgan_training

  Code for reproducing experiments in "Improved Training of Wasserstein GANs"

  Language:Python2.4k8092671

• tjwei/GANotebooks

  wgan, wgan2(improved, gp), infogan, and dcgan implementation in lasagne, keras, pytorch

  Language:Jupyter Notebook1.5k9913370

• jeanfeydy/geomloss

  Geometric loss functions between point clouds, images and volumes

  Language:Python607137362

• gpeyre/SinkhornAutoDiff

  Toolbox to integrate optimal transport loss functions using automatic differentiation and Sinkhorn's algorithm

  Language:Python43721439

• dilinwang820/Stein-Variational-Gradient-Descent

  code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"

  Language:Python387122122

• carsonip/Penguin-Subtitle-Player

  An open-source, cross-platform standalone subtitle player

  Language:C++305188538

• nicola-decao/MolGAN

  Tensorflow implementation of MolGAN: An implicit generative model for small molecular graphs

  Language:Python2628986

• OctoberChang/MMD-GAN

  MMD-GAN: Towards Deeper Understanding of Moment Matching Network

  Language:Python1994554

• openai/ot-gan

  Code for the paper "Improving GANs Using Optimal Transport"

  Language:Jupyter Notebook72159133

• musikisomorphie/swd

  unsupervised video and image generation

  Language:Python58346

• jeanfeydy/global-divergences

  MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.

  Language:Python542011

• bernhard-schmitzer/optimal-transport

  A collection of adaptive sparse multi-scale solvers for optimal transport and related optimization problems.

  Language:C++535017

• vndroid/shadowsocks-install

  a CLI Bash script to install shadowsocks server automatic for Debian / Ubuntu

  Language:Shell454415

• MichaelArbel/Scaled-MMD-GAN

  Scaled MMD GAN

  Language:Python36507

• gpeyre/2014-SISC-BregmanOT

  J-D. Benamou, G. Carlier, M. Cuturi, L. Nenna, G. Peyré. Iterative Bregman Projections for Regularized Transportation Problems. SIAM Journal on Scientific Computing, 37(2), pp. A1111–A1138, 2015.

  Language:TeX323014

• DartML/SteinGAN

  code for steinGAN - Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning

  Language:Python26407

• GiulsLu/Sinkhorn-Barycenters

  Sinkhorn Barycenters via Frank-Wolfe algorithm

  Language:Python24415

• gerrili1996/DRLR_NIPS2019_exp

  The MATLAB source code

  Language:MATLAB16203

• lewisKit/Amortized_SVGD

  Experiments of amortized stein variational gradient

  Language:Terra16318

• tomsercu/SobolevGAN-SSL

  Code accompanying the paper Sobolev GAN https://arxiv.org/abs/1711.04894

  Language:Python12412

• sebastian-claici/StochasticWassersteinBarycenters

  Implementation of the paper 'Stochastic Wasserstein Barycenters'

  Language:C++10524

• mstaib/stochastic-barycenter-code

  Supporting code for "Parallel Streaming Wasserstein Barycenters"

  Language:C++9411

• chanshing/sobolev_gan

  Pytorch implemention of Sobolev GAN (https://arxiv.org/abs/1711.04894)

  Language:Python8302

• Adoni/GANs

  GAN models implemented with PyTorch

  Language:Jupyter Notebook53

• kilianFatras/stochastic_opt_OT

  implementation of the paper "Stochastic Optimization for Large-scale Optimal Transport" (https://arxiv.org/pdf/1605.08527.pdf).

  Language:Python5403