MadryLab / glm_saga

Related projects ⓘ

Alternatives and complementary repositories for glm_saga

• MadryLab / modeldiff
  ModelDiff: A Framework for Comparing Learning Algorithms
  ☆53Updated last year
• js-d / sim_metric
  ☆35Updated last year
• ykwon0407 / beta_shapley
  Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)
  ☆40Updated 2 years ago
• MadryLab / DebuggableDeepNetworks
  ☆37Updated 3 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
• HazyResearch / mandoline
  (ICML 2021) Mandoline: Model Evaluation under Distribution Shift
  ☆31Updated 3 years ago
• blayes / WASP
  Scalable Bayes via Barycenter in Wasserstein Space
  ☆9Updated 7 years ago
• MadryLab / BREEDS-Benchmarks
  ☆55Updated 4 years ago
• ganguli-lab / degrees-of-freedom
  ☆36Updated 2 years ago
• jlko / active-testing
  Active and Sample-Efficient Model Evaluation
  ☆24Updated 3 years ago
• MadryLab / datamodels
  ☆23Updated last year
• izmailovpavel / spurious_feature_learning
  ☆41Updated last year
• google-research / heldout-influence-estimation
  ☆61Updated 3 years ago
• tml-epfl / sgd-sparse-features
  SGD with large step sizes learns sparse features [ICML 2023]
  ☆32Updated last year
• csinva / mdl-complexity
  MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".
  ☆18Updated last year
• bethgelab / InDomainGeneralizationBenchmark
  ☆33Updated 3 years ago
• MadryLab / failure-directions
  Distilling Model Failures as Directions in Latent Space
  ☆45Updated last year
• openopt / chop
  CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.
  ☆76Updated 8 months ago
• JonathanWenger / pycalib
  Non-Parametric Calibration for Classification (AISTATS 2020)
  ☆19Updated 2 years ago
• realityengines / post_hoc_debiasing
  ☆17Updated 4 years ago
• locuslab / perturbation_learning
  Learning perturbation sets for robust machine learning
  ☆64Updated 3 years ago
• uu-sml / calibration
  Python package for evaluating model calibration in classification
  ☆19Updated 5 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
• facebookresearch / BalancingGroups
  Simple data balancing baselines for worst-group-accuracy benchmarks.
  ☆41Updated last year
• g-benton / hessian-eff-dim
  Public Codebase for Rethinking Parameter Counting: Effective Dimensionality Revisited
  ☆36Updated last year
• JonasGeiping / dataaugs
  ☆17Updated 2 years ago
• facebookresearch / nbm-spam
  Training and evaluating NBM and SPAM for interpretable machine learning.
  ☆76Updated last year
• aangelopoulos / private_prediction_sets
  Wrap around any model to output differentially private prediction sets with finite sample validity on any dataset.
  ☆17Updated 8 months ago
• nitarshan / robust-generalization-measures
  Official code for "In Search of Robust Measures of Generalization" (NeurIPS 2020)
  ☆28Updated 3 years ago