Alternatives and similar repositories for dnn-topology:

Users that are interested in dnn-topology are comparing it to the libraries listed below

• g-benton / learning-invariances
  Codebase for Learning Invariances in Neural Networks
  ☆93Updated 2 years ago
• HazyResearch / model-patching
  Model Patching: Closing the Subgroup Performance Gap with Data Augmentation
  ☆42Updated 4 years ago
• singlasahil14 / barlow
  Code for the CVPR 2021 paper: Understanding Failures of Deep Networks via Robust Feature Extraction
  ☆35Updated 2 years ago
• bethgelab / InDomainGeneralizationBenchmark
  ☆34Updated 3 years ago
• akandykeller / TopographicVAE
  Official implementation of the paper "Topographic VAEs learn Equivariant Capsules"
  ☆78Updated 2 years ago
• vinayprabhu / Disentanglement_NEURIPS_2019
  On disentangling the menagerie of disentanglement papers
  ☆27Updated 5 years ago
• Cyanogenoid / dspn
  [NeurIPS 2019] Deep Set Prediction Networks
  ☆100Updated 4 years ago
• adebayoj / sanity_checks_saliency
  ☆109Updated 2 years ago
• ashafaei / OD-test
  OD-test: A Less Biased Evaluation of Out-of-Distribution (Outlier) Detectors (PyTorch)
  ☆62Updated last year
• rgeirhos / shortcut-perspective
  Figures & code from the paper "Shortcut Learning in Deep Neural Networks" (Nature Machine Intelligence 2020)
  ☆96Updated 2 years ago
• jxbz / fromage
  🧀 Pytorch code for the Fromage optimiser.
  ☆123Updated 7 months ago
• CUAI / Differentiable-Frechet-Mean
  [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).
  ☆54Updated 3 years ago
• lrjconan / RBP
  Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018
  ☆41Updated 6 years ago
• yassersouri / pytorch-deep-sets
  PyTorch re-implementation of parts of "Deep Sets" (NIPS 2017)
  ☆68Updated 6 years ago
• MadryLab / BREEDS-Benchmarks
  ☆54Updated 4 years ago
• ColinQiyangLi / LConvNet
  Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)
  ☆34Updated 4 years ago
• mpatacchiola / self-supervised-relational-reasoning
  Official PyTorch implementation of the paper "Self-Supervised Relational Reasoning for Representation Learning", NeurIPS 2020 Spotlight.
  ☆142Updated 10 months ago
• facebookresearch / jacobian_regularizer
  A pytorch implementation of our jacobian regularizer to encourage learning representations more robust to input perturbations.
  ☆125Updated last year
• chirag-agarwall / VOG
  Estimating Example Difficulty using Variance of Gradients
  ☆61Updated 2 years ago
• wiseodd / last_layer_laplace
  Last-layer Laplace approximation code examples
  ☆83Updated 3 years ago
• HazyResearch / hidden-stratification
  Combating hidden stratification with GEORGE
  ☆62Updated 3 years ago
• stanford-futuredata / equivariant-transformers
  Equivariant Transformer (ET) layers are image-to-image mappings that incorporate prior knowledge on invariances with respect to continuo…
  ☆89Updated 5 years ago
• twuilliam / nodes-info
  Resources on how to use the GPU clusters
  ☆31Updated 4 years ago
• AlexMeinke / certified-certain-uncertainty
  A way to achieve uniform confidence far away from the training data.
  ☆37Updated 3 years ago
• srebuffi / lsd-clusters
  ☆46Updated 2 years ago
• snap-stanford / crust
  [NeurIPS 2020] Coresets for Robust Training of Neural Networks against Noisy Labels
  ☆32Updated 3 years ago
• k9k2 / qSGD
  SGD and Ordered SGD codes for deep learning, SVM, and logistic regression
  ☆35Updated 4 years ago
• g-benton / loss-surface-simplexes
  ☆98Updated 3 years ago
• chingyaoc / fair-mixup
  ICLR 2021, Fair Mixup: Fairness via Interpolation
  ☆55Updated 3 years ago
• ruosongwang / CNTK
  Convolutional Neural Tangent Kernel
  ☆109Updated 5 years ago