Alternatives and similar repositories for Rethink-BiasVariance-Tradeoff:

Users that are interested in Rethink-BiasVariance-Tradeoff are comparing it to the libraries listed below

• yangarbiter / robust-local-lipschitz
  A Closer Look at Accuracy vs. Robustness
  ☆88Updated 3 years ago
• MadryLab / BREEDS-Benchmarks
  ☆54Updated 4 years ago
• wronnyhuang / gen-viz
  Code for the paper "Understanding Generalization through Visualizations"
  ☆60Updated 4 years ago
• avirmaux / lipEstimation
  ☆58Updated 2 years ago
• facebookresearch / BalancingGroups
  Simple data balancing baselines for worst-group-accuracy benchmarks.
  ☆42Updated last year
• chingyaoc / fair-mixup
  ICLR 2021, Fair Mixup: Fairness via Interpolation
  ☆55Updated 3 years ago
• hongyanz / TRADES-smoothing
  [JMLR] TRADES + random smoothing for certifiable robustness
  ☆14Updated 4 years ago
• prolearner / hypertorch
  ☆122Updated 10 months ago
• samuelstanton / gnosis
  Code to reproduce experiments from 'Does Knowledge Distillation Really Work' a paper which appeared in the 2021 NeurIPS proceedings.
  ☆33Updated last year
• parthnatekar / pgdl
  Winning Solution of the NeurIPS 2020 Competition on Predicting Generalization in Deep Learning
  ☆40Updated 3 years ago
• reiinakano / invariant-risk-minimization
  Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893
  ☆86Updated 5 years ago
• wiseodd / last_layer_laplace
  Last-layer Laplace approximation code examples
  ☆83Updated 3 years ago
• tonyduan / rs4a
  Randomized Smoothing of All Shapes and Sizes (ICML 2020).
  ☆52Updated 4 years ago
• locuslab / perturbation_learning
  Learning perturbation sets for robust machine learning
  ☆64Updated 3 years ago
• team-approx-bayes / fromp
  Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"
  ☆44Updated 4 years ago
• JonasGeiping / fullbatchtraining
  Training vision models with full-batch gradient descent and regularization
  ☆37Updated 2 years ago
• tml-epfl / understanding-sam
  Towards Understanding Sharpness-Aware Minimization [ICML 2022]
  ☆35Updated 2 years ago
• revbucket / geometric-certificates
  Geometric Certifications of Neural Nets
  ☆41Updated 2 years ago
• bneyshabur / generalization-bounds
  Computing various measures and generalization bounds on convolutional and fully connected networks
  ☆35Updated 6 years ago
• ppope / dimensions
  Code for "The Intrinsic Dimension of Images and Its Impact on Learning" - ICLR 2021 Spotlight https://openreview.net/forum?id=XJk19XzGq2J
  ☆68Updated 11 months ago
• preetum / cifar5m
  CIFAR-5m dataset
  ☆38Updated 4 years ago
• bobby-he / Neural_Tangent_Kernel
  ☆66Updated 6 years ago
• jfc43 / robust-ood-detection
  Robust Out-of-distribution Detection in Neural Networks
  ☆72Updated 2 years ago
• AlexMeinke / certified-certain-uncertainty
  A way to achieve uniform confidence far away from the training data.
  ☆37Updated 3 years ago
• cemanil / LNets
  Lipschitz Neural Networks described in "Sorting Out Lipschitz Function Approximation" (ICML 2019).
  ☆55Updated 4 years ago
• gibipara92 / learning-explanations-hard-to-vary
  Code to implement the AND-mask and geometric mean to do gradient based optimization, from the paper "Learning explanations that are hard …
  ☆39Updated 4 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
• tudor-berariu / fisher-information-matrix
  PyTorch implementation of FIM and empirical FIM
  ☆60Updated 6 years ago
• mpezeshki / Gradient_Starvation
  Gradient Starvation: A Learning Proclivity in Neural Networks
  ☆61Updated 4 years ago
• hendrycks / pre-training
  Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)
  ☆100Updated 3 years ago