Alternatives and similar repositories for DeepnetHessian:

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

• deep-lab / DeepnetHessian
  Measurements of Three-Level Hierarchical Structure in the Outliers in the Spectrum of Deepnet Hessians (ICML 2019)
  ☆17Updated 6 years ago
• revbucket / geometric-certificates
  Geometric Certifications of Neural Nets
  ☆41Updated 2 years ago
• MadryLab / DebuggableDeepNetworks
  ☆38Updated 3 years ago
• max-andr / provable-robustness-max-linear-regions
  Provable Robustness of ReLU networks via Maximization of Linear Regions [AISTATS 2019]
  ☆32Updated 4 years ago
• RuntianZ / doro
  Distributional and Outlier Robust Optimization (ICML 2021)
  ☆27Updated 3 years ago
• tonyduan / rs4a
  Randomized Smoothing of All Shapes and Sizes (ICML 2020).
  ☆52Updated 4 years ago
• MadryLab / BREEDS-Benchmarks
  ☆55Updated 4 years ago
• preetum / cifar5m
  CIFAR-5m dataset
  ☆38Updated 4 years ago
• ColinQiyangLi / LConvNet
  Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)
  ☆34Updated 4 years ago
• tml-epfl / sharpness-vs-generalization
  A modern look at the relationship between sharpness and generalization [ICML 2023]
  ☆43Updated last year
• locuslab / projected_sinkhorn
  ☆87Updated 9 months ago
• ytsmiling / lmt
  Public code for a paper "Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks."
  ☆34Updated 6 years ago
• wronnyhuang / gen-viz
  Code for the paper "Understanding Generalization through Visualizations"
  ☆60Updated 4 years ago
• yjhuangcd / local-lipschitz
  Official implementation for Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (NeurIPS, 2021).
  ☆23Updated 2 years ago
• bneyshabur / generalization-bounds
  Computing various measures and generalization bounds on convolutional and fully connected networks
  ☆35Updated 6 years ago
• facebookresearch / BalancingGroups
  Simple data balancing baselines for worst-group-accuracy benchmarks.
  ☆42Updated last year
• tml-epfl / understanding-sam
  Towards Understanding Sharpness-Aware Minimization [ICML 2022]
  ☆35Updated 2 years ago
• avirmaux / lipEstimation
  ☆58Updated 2 years ago
• harshays / simplicitybiaspitfalls
  The Pitfalls of Simplicity Bias in Neural Networks [NeurIPS 2020] (http://arxiv.org/abs/2006.07710v2)
  ☆39Updated last year
• litian96 / TERM
  Tilted Empirical Risk Minimization (ICLR '21)
  ☆59Updated last year
• locuslab / robust_union
  [ICML'20] Multi Steepest Descent (MSD) for robustness against the union of multiple perturbation models.
  ☆26Updated 9 months ago
• davidstutz / confidence-calibrated-adversarial-training
  Implementation of Confidence-Calibrated Adversarial Training (CCAT).
  ☆45Updated 4 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
• Faruk-Ahmed / predictive_group_invariance
  ☆34Updated 4 years ago
• ssagawa / overparam_spur_corr
  An Investigation of Why Overparameterization Exacerbates Spurious Correlations
  ☆31Updated 4 years ago
• jonasrauber / linear-region-attack
  A powerful white-box adversarial attack that exploits knowledge about the geometry of neural networks to find minimal adversarial perturb…
  ☆12Updated 4 years ago
• ftramer / Excessive-Invariance
  Source code for the paper "Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness"
  ☆25Updated 5 years ago
• locuslab / orthogonal-convolutions
  Implementations of orthogonal and semi-orthogonal convolutions in the Fourier domain with applications to adversarial robustness
  ☆44Updated 4 years ago
• k9k2 / qSGD
  SGD and Ordered SGD codes for deep learning, SVM, and logistic regression
  ☆35Updated 4 years ago
• AKuzina / attack_vae
  Diagnosing Vulnerability of Variational Auto-Encoders to Adversarial Attacks
  ☆14Updated 3 years ago