Alternatives and similar repositories for fair_noise_as_targets

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

• MSusik / Inhibited-softmax
  Repository with code for paper "Inhibited Softmax for Uncertainty Estimation in Neural Networks"
  ☆25Updated 6 years ago
• christopher-beckham / amr
  Official adversarial mixup resynthesis repository
  ☆35Updated 5 years ago
• SamsungLabs / deep-weight-prior
  The Deep Weight Prior, ICLR 2019
  ☆45Updated 4 years ago
• ron-amit / meta-learning-adjusting-priors
  Implementation of the paper "Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory", Ron Amit and Ron Meir, ICML 2018
  ☆22Updated 5 years ago
• ColinQiyangLi / LConvNet
  Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)
  ☆35Updated 4 years ago
• srebuffi / lsd-clusters
  ☆46Updated 2 years ago
• gabrielhuang / centroid-networks
  Code for the Paper "Centroid Networks for Few-Shot Clustering and Unsupervised Few-Shot Classification"
  ☆23Updated 5 years ago
• ermongroup / f-wgan
  Code for "Bridging the Gap between f-GANs and Wasserstein GANs", ICML 2020
  ☆14Updated 4 years ago
• BorealisAI / bre-gan
  Code for ICLR2018 paper: Improving GAN Training via Binarized Representation Entropy (BRE) Regularization - Y. Cao · W Ding · Y.C. Lui · …
  ☆20Updated 6 years ago
• srebuffi / semisup_scarse
  PyTorch implementation of Semi-Supervised Learning with Scarce Annotations https://arxiv.org/pdf/1905.08845.pdf
  ☆13Updated 5 years ago
• 962086838 / code-for-Asymmetric-Valley
  This repo contains the code used for NeurIPS 2019 paper "Asymmetric Valleys: Beyond Sharp and Flat Local Minima".
  ☆14Updated 5 years ago
• yaohungt / Adaptive-Regularization-Neural-Network
  [NeurIPS'19] [PyTorch] Adaptive Regularization in NN
  ☆68Updated 5 years ago
• ucla-vision / information-dropout
  Implementation of Information Dropout
  ☆39Updated 7 years ago
• da-molchanov / variance-networks
  Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019
  ☆39Updated 5 years ago
• joelouismarino / iterative_inference
  Implementation of iterative inference in deep latent variable models
  ☆43Updated 5 years ago
• RobRomijnders / bayes_nn
  Uncertainty interpretations of the neural network
  ☆32Updated 7 years ago
• k9k2 / qSGD
  SGD and Ordered SGD codes for deep learning, SVM, and logistic regression
  ☆35Updated 4 years ago
• ruthcfong / net2vec
  Code for Net2Vec: Quantifying and Explaining how Concepts are Encoded by Filters in Deep Neural Networks
  ☆30Updated 7 years ago
• fmu2 / gradfeat20
  Gradients as Features for Deep Representation Learning
  ☆43Updated 5 years ago
• takerum / vat_chainer
  Implementation of Virtual adversarial training with chainer
  ☆40Updated 7 years ago
• icml-mcbn / mcbn
  ☆53Updated 7 years ago
• BB-UCL / Lasagne
  ☆13Updated 7 years ago
• ashafaei / OD-test
  OD-test: A Less Biased Evaluation of Out-of-Distribution (Outlier) Detectors (PyTorch)
  ☆62Updated last year
• RAIVNLab / FLUID
  ☆24Updated 2 years ago
• odegeasslbc / pytorch-IBGAN
  A pytorch implementation of Information Bottleneck GAN
  ☆28Updated 6 years ago
• bneyshabur / over-parametrization
  Computing various norms/measures on over-parametrized neural networks
  ☆49Updated 6 years ago
• haebeom-lee / dropmax
  Tensorflow implementation of DropMax: Adaptive Variational Softmax (NeurIPS2018)
  ☆18Updated 5 years ago
• davidstutz / cvpr2019-adversarial-robustness
  CVPR 2019 paper "Disentangling Adversarial Robustness and Generalization".
  ☆14Updated 5 years ago
• vsyrgkanis / optimistic_GAN_training
  ☆46Updated 7 years ago
• asteroidhouse / self-tuning-networks
  Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088
  ☆54Updated 5 years ago