Alternatives and similar repositories for GSAM

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

• dydjw9 / Efficient_SAM
  ☆58Updated 2 years ago
• htdt / self-supervised
  Whitening for Self-Supervised Representation Learning | Official repository
  ☆130Updated 2 years ago
• facebookresearch / directclr
  Code used in "Understanding Dimensional Collapse in Contrastive Self-supervised Learning" paper.
  ☆79Updated 2 years ago
• libffcv / ffcv-imagenet
  Train ImageNet *fast* in 500 lines of code with FFCV
  ☆144Updated last year
• YugeTen / fish
  Official implementation of paper Gradient Matching for Domain Generalization
  ☆122Updated 3 years ago
• andyzoujm / pixmix
  PixMix: Dreamlike Pictures Comprehensively Improve Safety Measures (CVPR 2022)
  ☆108Updated 3 years ago
• alexrame / fishr
  Official PyTorch implementation of the Fishr regularization for out-of-distribution generalization
  ☆87Updated 3 years ago
• KellerJordan / REPAIR
  Code release for REPAIR: REnormalizing Permuted Activations for Interpolation Repair
  ☆48Updated last year
• adrianjav / rotograd
  Official Pytorch's implementation of RotoGrad
  ☆80Updated 2 years ago
• YugeTen / adios
  ☆65Updated 3 years ago
• mpezeshki / Gradient_Starvation
  Gradient Starvation: A Learning Proclivity in Neural Networks
  ☆61Updated 4 years ago
• allenai / ViRB
  Visual Representation Learning Benchmark for Self-Supervised Models
  ☆35Updated last year
• PolinaKirichenko / deep_feature_reweighting
  ☆108Updated last year
• yaohungt / Barlow-Twins-HSIC
  ☆57Updated 3 years ago
• Weixin-Liang / MetaShift
  MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts (ICLR 2022)
  ☆109Updated 2 years ago
• samuelstanton / gnosis
  Code to reproduce experiments from 'Does Knowledge Distillation Really Work' a paper which appeared in the 2021 NeurIPS proceedings.
  ☆33Updated last year
• google-research / understanding-curricula
  ☆34Updated 2 months ago
• snu-mllab / Co-Mixup
  Official PyTorch implementation of "Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity" (ICLR'21 Oral)
  ☆106Updated 3 years ago
• mansheej / data_diet
  ☆108Updated 2 years ago
• hongxin001 / logitnorm_ood
  Official code for ICML 2022: Mitigating Neural Network Overconfidence with Logit Normalization
  ☆150Updated 3 years ago
• AvivNavon / AuxiLearn
  Official implementation of Auxiliary Learning by Implicit Differentiation [ICLR 2021]
  ☆85Updated last year
• VITA-Group / CV_LTH_Pre-training
  [CVPR 2021] "The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models" Tianlong Chen, Jon…
  ☆68Updated 2 years ago
• YannDubs / Invariant-Self-Supervised-Learning
  Pytorch code for "Improving Self-Supervised Learning by Characterizing Idealized Representations"
  ☆41Updated 2 years ago
• songweige / Contrastive-Learning-with-Non-Semantic-Negatives
  Robust Contrastive Learning Using Negative Samples with Diminished Semantics (NeurIPS 2021)
  ☆39Updated 3 years ago
• yolky / RFAD
  Code for the paper "Efficient Dataset Distillation using Random Feature Approximation"
  ☆37Updated 2 years ago
• somepago / dbViz
  The official PyTorch implementation - Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from t…
  ☆80Updated 3 years ago
• LayneH / self-adaptive-training
  [TPAMI2022 & NeurIPS2020] Official implementation of Self-Adaptive Training
  ☆129Updated 3 years ago
• VITA-Group / Nasty-Teacher
  [ICLR 2021 Spotlight Oral] "Undistillable: Making A Nasty Teacher That CANNOT teach students", Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Che…
  ☆82Updated 3 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
• VITA-Group / AugMax
  [NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Z…
  ☆125Updated 3 years ago