Alternatives and similar repositories for prepare-oxford-faces

Users that are interested in prepare-oxford-faces are comparing it to the libraries listed below

• irapha / replayed_distillation
  Implementation of Data-free Knowledge Distillation for Deep Neural Networks (on arxiv!)
  ☆81Updated 7 years ago
• stevenygd / SWALP
  Code for paper "SWALP: Stochastic Weight Averaging forLow-Precision Training".
  ☆62Updated 6 years ago
• eladhoffer / norm_matters
  ☆23Updated 7 years ago
• labsix / adversarial-logit-pairing-analysis
  Analysis of Adversarial Logit Pairing
  ☆60Updated 7 years ago
• Prinsphield / Adversarial_Reprogramming
  Adversarial Reprogramming of Neural Networks
  ☆33Updated 7 years ago
• lottery-ticket / rewinding-iclr20-public
  ☆69Updated 5 years ago
• angelajiang / SelectiveBackprop
  SelectiveBackprop accelerates training by dynamically prioritizing useful examples with high loss
  ☆32Updated 5 years ago
• AngusG / cleverhans-attacking-bnns
  Source for paper "Attacking Binarized Neural Networks"
  ☆23Updated 7 years ago
• shashankkotyan / RobustArchitectureSearch
  This github repository contains the official code for the paper, "Evolving Robust Neural Architectures to Defend from Adversarial Attacks…
  ☆20Updated last year
• sibosutd / feature-distillation
  Python implementation for paper: Feature Distillation: DNN-Oriented JPEG Compression Against Adversarial Examples
  ☆11Updated 7 years ago
• microsoft / denoised-smoothing
  Provably defending pretrained classifiers including the Azure, Google, AWS, and Clarifai APIs
  ☆97Updated 4 years ago
• oval-group / dfw
  Implementation of the Deep Frank-Wolfe Algorithm -- Pytorch
  ☆63Updated 4 years ago
• anubhavashok / N2N
  ☆55Updated 6 years ago
• facebookresearch / fisher_information_loss
  This code reproduces the results of the paper, "Measuring Data Leakage in Machine-Learning Models with Fisher Information"
  ☆50Updated 4 years ago
• val-iisc / fast-feature-fool
  Data independent universal adversarial perturbations
  ☆63Updated 5 years ago
• RuishanLiu / GAN-TSC
  ☆11Updated 5 years ago
• zhongyy / Adversarial_MTER
  Code for ICCV2019 paper《Adversarial Learning with Margin-based Triplet Embedding Regularization》
  ☆30Updated 6 years ago
• BayesWatch / pytorch-blockswap
  Code for BlockSwap (ICLR 2020).
  ☆33Updated 4 years ago
• VITA-Group / ATMC
  [NeurIPS'2019] Shupeng Gui, Haotao Wang, Haichuan Yang, Chen Yu, Zhangyang Wang, Ji Liu, “Model Compression with Adversarial Robustness: …
  ☆49Updated 3 years ago
• MadryLab / robustness_applications
  Notebooks for reproducing the paper "Computer Vision with a Single (Robust) Classifier"
  ☆129Updated 6 years ago
• eladhoffer / fix_your_classifier
  ☆34Updated 7 years ago
• MatthieuCourbariaux / 8-bit-deep-learning
  Training neural networks with 8-bit computations
  ☆28Updated 9 years ago
• ruthcfong / net2vec
  Code for Net2Vec: Quantifying and Explaining how Concepts are Encoded by Filters in Deep Neural Networks
  ☆30Updated 7 years ago
• Healbadbad / curveball-pytorch
  An Implementation of "Small steps and giant leaps: Minimal Newton solvers for Deep Learning" In pytorch
  ☆21Updated 7 years ago
• rwightman / pytorch-nips2017-attack-example
  A PyTorch baseline attack example for the NIPS 2017 adversarial competition
  ☆86Updated 8 years ago
• joe-siyuan-qiao / NeuralRejuvenation-CVPR19
  Neural Rejuvenation: Improving Deep Network Training by Enhancing Computational Resource Utilization at CVPR'19
  ☆48Updated 6 years ago
• McDonnell-Research-Lab / 1-bit-per-weight
  Training wide residual networks for deployment using a single bit for each weight - Official Code Repository for ICLR 2018 Published Pape…
  ☆36Updated 5 years ago
• huanzhang12 / Adversarial_Survey
  Robustness vs Accuracy Survey on ImageNet
  ☆99Updated 4 years ago
• LTS4 / SparseFool
  A fast sparse attack on deep neural networks.
  ☆50Updated 5 years ago
• MadryLab / dataset-replication-analysis
  ☆25Updated 5 years ago