Alternatives and similar repositories for hGAN

Users that are interested in hGAN are comparing it to the libraries listed below

• musikisomorphie / swd
  unsupervised video and image generation
  ☆57Updated 5 years ago
• icml-mcbn / mcbn
  ☆53Updated 7 years ago
• Newbeeer / orthogonal_classifier
  Code for ICLR 2022 Paper, "Controlling Directions Orthogonal to a Classifier"
  ☆35Updated 2 years ago
• autonomousvision / counterfactual_generative_networks
  [ICLR'21] Counterfactual Generative Networks
  ☆107Updated 4 years ago
• chingyaoc / fair-mixup
  ICLR 2021, Fair Mixup: Fairness via Interpolation
  ☆59Updated 4 years ago
• henrikmarklund / arm
  ☆83Updated 2 years ago
• fjxmlzn / PacGAN
  [NeurIPS 2018] [JSAIT] PacGAN: The power of two samples in generative adversarial networks
  ☆82Updated 5 years ago
• ritheshkumar95 / energy_based_generative_models
  PyTorch code accompanying our paper on Maximum Entropy Generators for Energy-Based Models
  ☆155Updated 6 years ago
• ermongroup / f-wgan
  Code for "Bridging the Gap between f-GANs and Wasserstein GANs", ICML 2020
  ☆14Updated 5 years ago
• ColinQiyangLi / LConvNet
  Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)
  ☆36Updated 5 years ago
• yogeshbalaji / robustOT
  Robust Optimal Transport code
  ☆43Updated 3 years ago
• google-research / s4l
  Tensorflow implementation of S4L: Self-Supervised Semi-Supervised Learning
  ☆95Updated 6 years ago
• eifuentes / swae-pytorch
  Implementation of the Sliced Wasserstein Autoencoder using PyTorch
  ☆101Updated 7 years ago
• bpucla / latent-space-EBM-prior
  ☆38Updated 5 years ago
• lin-shuyu / ladder-latent-data-distribution-modelling
  In this paper, we show that the performance of a learnt generative model is closely related to the model's ability to accurately represen…
  ☆41Updated 4 years ago
• stanford-futuredata / sinkhorn-label-allocation
  Sinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms. The SLA algorithm is described in fu…
  ☆53Updated 4 years ago
• parthnatekar / pgdl
  Winning Solution of the NeurIPS 2020 Competition on Predicting Generalization in Deep Learning
  ☆41Updated 4 years ago
• henrygouk / mars-finetuning
  ☆19Updated 5 years ago
• yoonholee / MT-net
  Code accompanying the ICML-2018 paper "Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace"
  ☆38Updated 7 years ago
• rythei / PyTorchOT
  implements optimal transport algorithms in pytorch
  ☆104Updated 3 years ago
• fmu2 / gradfeat20
  Gradients as Features for Deep Representation Learning
  ☆43Updated 5 years ago
• maremun / swg
  Sliced Wasserstein Generator
  ☆22Updated 7 years ago
• ucla-vision / information-dropout
  Implementation of Information Dropout
  ☆39Updated 8 years ago
• kylehkhsu / cactus-protonets
  Code for Unsupervised Learning via Meta-Learning.
  ☆67Updated 5 years ago
• richardwth / MMD-GAN
  Improving MMD-GAN training with repulsive loss function
  ☆90Updated 3 years ago
• KaosEngineer / PriorNetworks-OLD
  ☆42Updated 6 years ago
• Cyanogenoid / fspool
  [ICLR 2020] FSPool: Learning Set Representations with Featurewise Sort Pooling
  ☆41Updated 2 years ago
• hytseng0509 / DropGrad
  Regularizing Meta-Learning via Gradient Dropout
  ☆53Updated 5 years ago
• zhuxinqimac / PS-SC
  Code for CVPR2021 paper 'Where and What? Examining Interpretable Disentangled Representations'.
  ☆45Updated 3 years ago
• bethgelab / slow_disentanglement
  Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding
  ☆73Updated 4 years ago