Alternatives and similar repositories for dataset-interfaces

Users that are interested in dataset-interfaces are comparing it to the libraries listed below

• Hritikbansal / generative-robustness
  Create generated datasets and train robust classifiers
  ☆35Updated last year
• tsb0601 / MultiMon
  ☆24Updated 2 years ago
• youranonymousefriend / plugininversion
  Official Implementation for PlugIn Inversion
  ☆16Updated 3 years ago
• brendel-group / clip-ood
  Official code for the paper "Does CLIP's Generalization Performance Mainly Stem from High Train-Test Similarity?" (ICLR 2024)
  ☆10Updated 10 months ago
• MadryLab / journey-TRAK
  Code for the paper "The Journey, Not the Destination: How Data Guides Diffusion Models"
  ☆22Updated last year
• ml-research / Fair-Diffusion
  ☆46Updated last year
• modestyachts / cifar-10.2
  Host CIFAR-10.2 Data Set
  ☆13Updated 3 years ago
• yuhui-zh15 / drml
  Official Code Release for "Diagnosing and Rectifying Vision Models using Language" (ICLR 2023)
  ☆34Updated 2 years ago
• Saehyung-Lee / DCC
  This repository is the official implementation of Dataset Condensation with Contrastive Signals (DCC), accepted at ICML 2022.
  ☆21Updated 3 years ago
• facebookresearch / Whac-A-Mole
  Code for the paper "A Whac-A-Mole Dilemma Shortcuts Come in Multiples Where Mitigating One Amplifies Others"
  ☆48Updated 11 months ago
• locuslab / T-MARS
  Code for T-MARS data filtering
  ☆35Updated last year
• Newbeeer / orthogonal_classifier
  Code for ICLR 2022 Paper, "Controlling Directions Orthogonal to a Classifier"
  ☆35Updated 2 years ago
• abarbu / objectnet-template-pytorch
  baseline mode for the ObjectNet competition
  ☆17Updated 4 years ago
• modestyachts / ImageNetV2_pytorch
  ImageNetV2 Pytorch Dataset
  ☆41Updated 2 years ago
• tml-epfl / sharpness-vs-generalization
  A modern look at the relationship between sharpness and generalization [ICML 2023]
  ☆43Updated last year
• singlasahil14 / salient_imagenet
  Code for the ICLR 2022 paper. Salient Imagenet: How to discover spurious features in deep learning?
  ☆40Updated 2 years ago
• chingyaoc / debias_vl
  Code for Debiasing Vision-Language Models via Biased Prompts
  ☆56Updated 2 years ago
• chawins / adv-part-model
  Code for a research paper "Part-Based Models Improve Adversarial Robustness" (ICLR 2023)
  ☆23Updated last year
• KingJamesSong / RankFeat
  NeurIPS22 "RankFeat: Rank-1 Feature Removal for Out-of-distribution Detection" and T-PAMI Extension
  ☆19Updated 4 months ago
• ryoungj / optdom
  [ICLR'22] Self-supervised learning optimally robust representations for domain shift.
  ☆24Updated 3 years ago
• uvavision / Balanced-Datasets-Are-Not-Enough
  [ICCV 2019] Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations
  ☆31Updated 3 years ago
• YuxinWenRick / diffusion_memorization
  Official repo for Detecting, Explaining, and Mitigating Memorization in Diffusion Models (ICLR 2024)
  ☆75Updated last year
• alinlab / b2t
  Bias-to-Text: Debiasing Unknown Visual Biases through Language Interpretation
  ☆31Updated 2 years ago
• evandez / neuron-descriptions
  Natural Language Descriptions of Deep Visual Features, ICLR 2022
  ☆65Updated last year
• JonasGeiping / dataaugs
  ☆18Updated 2 years ago
• princetonvisualai / HIVE
  HIVE: Evaluating the Human Interpretability of Visual Explanations (ECCV 2022)
  ☆20Updated 2 years ago
• hamidkazemi22 / CLIPInversion
  What do we learn from inverting CLIP models?
  ☆55Updated last year
• NYU-DICE-Lab / circumventing-concept-erasure
  ☆20Updated last year
• shift-happens-benchmark / icml-2022
  Crowdsourcing metrics and test datasets beyond ImageNet (ICML 2022 workshop)
  ☆37Updated last year
• liuchen11 / AdversaryLossLandscape
  On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]
  ☆36Updated 3 years ago