Alternatives and similar repositories for LabelBench

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

• aengusl / spawrious
  ☆27Updated last year
• izmailovpavel / spurious_feature_learning
  ☆45Updated 2 years ago
• AnanyaKumar / transfer_learning
  Framework code with wandb, checkpointing, logging, configs, experimental protocols. Useful for fine-tuning models or training from scratc…
  ☆151Updated 2 years ago
• PolinaKirichenko / deep_feature_reweighting
  ☆107Updated last year
• google-deepmind / distribution_shift_framework
  This repository contains the code of the distribution shift framework presented in A Fine-Grained Analysis on Distribution Shift (Wiles e…
  ☆83Updated 3 weeks ago
• facebookresearch / Whac-A-Mole
  Code for the paper "A Whac-A-Mole Dilemma Shortcuts Come in Multiples Where Mitigating One Amplifies Others"
  ☆49Updated last year
• mpagli / Agree-to-Disagree
  Repo for the paper: "Agree to Disagree: Diversity through Disagreement for Better Transferability"
  ☆36Updated 2 years ago
• rgeirhos / dataset-pruning-metrics
  Metrics for "Beyond neural scaling laws: beating power law scaling via data pruning " (NeurIPS 2022 Outstanding Paper Award)
  ☆56Updated 2 years ago
• somepago / dbViz
  The official PyTorch implementation - Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from t…
  ☆79Updated 3 years ago
• huaxiuyao / LISA
  LISA for ICML 2022
  ☆50Updated 2 years ago
• Weixin-Liang / MetaShift
  MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts (ICLR 2022)
  ☆109Updated 2 years ago
• tding1 / Neural-Collapse
  [NeurIPS 2021] A Geometric Analysis of Neural Collapse with Unconstrained Features
  ☆57Updated 2 years ago
• zeyademam / active_learning
  Code for Active Learning at The ImageNet Scale. This repository implements many popular active learning algorithms and allows training wi…
  ☆53Updated 3 years ago
• acmi-lab / RLSbench
  Code and results accompanying our paper titled RLSbench: Domain Adaptation under Relaxed Label Shift
  ☆34Updated last year
• MadryLab / datamodels-data
  Data for "Datamodels: Predicting Predictions with Training Data"
  ☆97Updated 2 years ago
• YyzHarry / SubpopBench
  [ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift
  ☆108Updated 2 years ago
• yolky / RFAD
  Code for the paper "Efficient Dataset Distillation using Random Feature Approximation"
  ☆37Updated 2 years ago
• anniesch / surgical-finetuning
  Code for "Surgical Fine-Tuning Improves Adaptation to Distribution Shifts" published at ICLR 2023
  ☆28Updated 2 years ago
• tml-epfl / sam-low-rank-features
  Sharpness-Aware Minimization Leads to Low-Rank Features [NeurIPS 2023]
  ☆28Updated last year
• mansheej / data_diet
  ☆108Updated 2 years ago
• alexrame / diwa
  DiWA: Diverse Weight Averaging for Out-of-Distribution Generalization
  ☆31Updated 2 years ago
• andrijazz / ash
  Code release for paper Extremely Simple Activation Shaping for Out-of-Distribution Detection
  ☆54Updated 10 months ago
• ryoungj / optdom
  [ICLR'22] Self-supervised learning optimally robust representations for domain shift.
  ☆24Updated 3 years ago
• Vanint / Core-tuning
  This repository is the official implementation of Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regulari…
  ☆21Updated 2 years ago
• modestyachts / ImageNetV2_pytorch
  ImageNetV2 Pytorch Dataset
  ☆41Updated 2 years ago
• BigML-CS-UCLA / SpuCo
  SpuCo is a Python package developed to further research to address spurious correlations.
  ☆24Updated 6 months ago
• joshr17 / IFM
  Code for paper "Can contrastive learning avoid shortcut solutions?" NeurIPS 2021.
  ☆47Updated 3 years ago
• sjoshi804 / sas-data-efficient-contrastive-learning
  Official Code for ICML 2023 Data-Efficient Contrastive Self-supervised Learning
  ☆32Updated last year
• huaxiuyao / Wild-Time
  Benchmark for Natural Temporal Distribution Shift (NeurIPS 2022)
  ☆67Updated 2 years ago
• Wuyxin / DISC
  (ICML 2023) Discover and Cure: Concept-aware Mitigation of Spurious Correlation
  ☆41Updated last year