Alternatives and similar repositories for dataset-pruning-metrics:

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

• naotoo1 / Beyond-Neural-Scaling
  Implementation of Beyond Neural Scaling beating power laws for deep models and prototype-based models
  ☆33Updated 2 weeks ago
• Saehyung-Lee / DCC
  This repository is the official implementation of Dataset Condensation with Contrastive Signals (DCC), accepted at ICML 2022.
  ☆21Updated 2 years ago
• yongchaoz / FRePo
  Official Code for Dataset Distillation using Neural Feature Regression (NeurIPS 2022)
  ☆47Updated 2 years ago
• princetonvisualai / RememberThePast-DatasetDistillation
  ☆39Updated 2 years ago
• modestyachts / ImageNetV2_pytorch
  ImageNetV2 Pytorch Dataset
  ☆41Updated last year
• yolky / RFAD
  Code for the paper "Efficient Dataset Distillation using Random Feature Approximation"
  ☆37Updated 2 years ago
• yu-rp / Distribution-Shift-Iverson
  ☆42Updated last year
• AngusDujw / FTD-distillation
  The code of the paper "Minimizing the Accumulated Trajectory Error to Improve Dataset Distillation" (CVPR2023)
  ☆40Updated 2 years ago
• haohang96 / bingo
  Bag of Instances Aggregation Boosts Self-supervised Distillation (ICLR 2022)
  ☆33Updated 2 years ago
• dydjw9 / Efficient_SAM
  ☆57Updated 2 years ago
• tml-epfl / sam-low-rank-features
  Sharpness-Aware Minimization Leads to Low-Rank Features [NeurIPS 2023]
  ☆28Updated last year
• mchiquier / llm-mutate
  ☆13Updated 6 months ago
• zhangq327 / U-MAE
  Official Code for NeurIPS 2022 Paper: How Mask Matters: Towards Theoretical Understandings of Masked Autoencoders
  ☆58Updated last year
• deeplearning-wisc / poem
  PyTorch implementation of POEM (Out-of-distribution detection with posterior sampling), ICML 2022
  ☆28Updated last year
• boyazeng / understand_bias
  Code release for "Understanding Bias in Large-Scale Visual Datasets"
  ☆20Updated 4 months ago
• TencentARC / pi-Tuning
  Official code for "pi-Tuning: Transferring Multimodal Foundation Models with Optimal Multi-task Interpolation", ICML 2023.
  ☆32Updated last year
• justincui03 / dc_benchmark
  ☆86Updated 2 years ago
• mpagli / Agree-to-Disagree
  Repo for the paper: "Agree to Disagree: Diversity through Disagreement for Better Transferability"
  ☆36Updated 2 years ago
• YUE-FAN / CoSSL
  Official PyTorch Implementation of "CoSSL: Co-Learning of Representation and Classifier for Imbalanced Semi-Supervised Learning" (CVPR 20…
  ☆53Updated 2 years ago
• yukimasano / single-img-extrapolating
  Repo for the paper "Extrapolating from a Single Image to a Thousand Classes using Distillation"
  ☆36Updated 8 months ago
• aengusl / spawrious
  ☆26Updated last year
• showlab / datacentric.vlp
  Compress conventional Vision-Language Pre-training data
  ☆49Updated last year
• deeplearning-wisc / Spurious_OOD
  ☆22Updated 2 years ago
• MingSun-Tse / Good-DA-in-KD
  [NeurIPS'22] What Makes a "Good" Data Augmentation in Knowledge Distillation -- A Statistical Perspective
  ☆36Updated 2 years ago
• ZichenMiao / CL_Atom_Swapping
  ICLR 2022 (Spolight): Continual Learning With Filter Atom Swapping
  ☆16Updated last year
• deeplearning-wisc / gradnorm_ood
  On the Importance of Gradients for Detecting Distributional Shifts in the Wild
  ☆56Updated 2 years ago
• snu-mllab / Efficient-Dataset-Condensation
  Official PyTorch implementation of "Dataset Condensation via Efficient Synthetic-Data Parameterization" (ICML'22)
  ☆112Updated last year
• vita-epfl / ttt-plus-plus
  [NeurIPS21] TTT++: When Does Self-supervised Test-time Training Fail or Thrive?
  ☆65Updated 3 years ago
• Hritikbansal / generative-robustness
  Create generated datasets and train robust classifiers
  ☆34Updated last year
• tmllab / 2021_NeurIPS_PES
  ☆29Updated 2 years ago