Alternatives and similar repositories for fast-axiomatic-attribution

Users that are interested in fast-axiomatic-attribution are comparing it to the libraries listed below

• js-d / sim_metric
  ☆37Updated last year
• MadryLab / ImageNetMultiLabel
  Fine-grained ImageNet annotations
  ☆29Updated 5 years ago
• rtaori / data_feedback
  Code for the paper "Data Feedback Loops: Model-driven Amplification of Dataset Biases"
  ☆16Updated 3 years ago
• rehg-lab / CLRec
  Pytorch implementation for "The Surprising Positive Knowledge Transfer in Continual 3D Object Shape Reconstruction"
  ☆33Updated 3 years ago
• mfederici / dsit
  Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"
  ☆25Updated 3 years ago
• alexrame / diwa
  DiWA: Diverse Weight Averaging for Out-of-Distribution Generalization
  ☆31Updated 2 years ago
• KempnerInstitute / llm_uncertainty
  Code for the paper "Distinguishing the Knowable from the Unknowable with Language Models"
  ☆10Updated last year
• yaohungt / Pointwise_Dependency_Neural_Estimation
  ☆20Updated 5 years ago
• MadryLab / datamodels
  ☆30Updated 2 years ago
• inspire-group / robustness-via-transport
  ☆12Updated 5 years ago
• uiuctml / fair-classification
  Post-processing for fair classification
  ☆16Updated 2 months ago
• MadryLab / datamodels-data
  Data for "Datamodels: Predicting Predictions with Training Data"
  ☆97Updated 2 years ago
• socialfoundations / benchbench
  BenchBench is a Python package to evaluate multi-task benchmarks.
  ☆16Updated last year
• harshays / inputgradients
  Do input gradients highlight discriminative features? [NeurIPS 2021] (https://arxiv.org/abs/2102.12781)
  ☆13Updated 2 years ago
• hlml / fortuitous_forgetting
  ☆19Updated 3 years ago
• dmitrykazhdan / concept-based-xai
  Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI
  ☆54Updated 3 years ago
• YilunZhou / optimal-active-learning
  Code repository for the AISTATS 2021 paper "Towards Understanding the Optimal Behaviors of Deep Active Learning Algorithms"
  ☆15Updated 4 years ago
• facebookresearch / ModelRatatouille
  Recycling diverse models
  ☆45Updated 2 years ago
• Kennethborup / self_distillation
  Self-Distillation with weighted ground-truth targets; ResNet and Kernel Ridge Regression
  ☆19Updated 3 years ago
• acmi-lab / RLSbench
  Code and results accompanying our paper titled RLSbench: Domain Adaptation under Relaxed Label Shift
  ☆35Updated 2 years ago
• GDPlumb / ExpO
  Explanation Optimization
  ☆13Updated 4 years ago
• MadryLab / modeldiff
  ModelDiff: A Framework for Comparing Learning Algorithms
  ☆59Updated 2 years ago
• ElisaNguyen / bayesian-tda
  Code for NeurIPS'23 paper "A Bayesian Approach To Analysing Training Data Attribution In Deep Learning"
  ☆17Updated last year
• HazyResearch / model-patching
  Model Patching: Closing the Subgroup Performance Gap with Data Augmentation
  ☆42Updated 4 years ago
• zackchase / label_shift
  A simple algorithm to identify and correct for label shift.
  ☆22Updated 7 years ago
• nitarshan / robust-generalization-measures
  Official code for "In Search of Robust Measures of Generalization" (NeurIPS 2020)
  ☆28Updated 4 years ago
• MadryLab / dataset-replication-analysis
  ☆25Updated 5 years ago
• MadryLab / DebuggableDeepNetworks
  ☆38Updated 4 years ago
• j-cb / GOOD
  Provable Worst Case Guarantees for the Detection of Out-of-Distribution Data
  ☆13Updated 3 years ago
• shwinshaker / LipGrow
  An adaptive training algorithm for residual network
  ☆17Updated 5 years ago