Alternatives and similar repositories for dbViz:

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

• dedeswim / vits-robustness-torch
  Code for the paper "A Light Recipe to Train Robust Vision Transformers" [SaTML 2023]
  ☆52Updated 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
• 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
• yangarbiter / robust-local-lipschitz
  A Closer Look at Accuracy vs. Robustness
  ☆88Updated 3 years ago
• MadryLab / BREEDS-Benchmarks
  ☆55Updated 4 years ago
• VITA-Group / Alleviate-Robust-Overfitting
  [ICLR 2021] "Robust Overfitting may be mitigated by properly learned smoothening" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, Shiyu Chan…
  ☆46Updated 3 years ago
• deeplearning-wisc / gradnorm_ood
  On the Importance of Gradients for Detecting Distributional Shifts in the Wild
  ☆56Updated 2 years ago
• yolky / RFAD
  Code for the paper "Efficient Dataset Distillation using Random Feature Approximation"
  ☆37Updated 2 years ago
• ondrejbohdal / label-distillation
  Official PyTorch implementation of “Flexible Dataset Distillation: Learn Labels Instead of Images”
  ☆42Updated 4 years ago
• modestyachts / imagenet-testbed
  ImageNet Testbed, associated with the paper "Measuring Robustness to Natural Distribution Shifts in Image Classification."
  ☆118Updated last year
• LijieFan / AdvCL
  [NeurIPS 2021] “When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?”
  ☆48Updated 3 years ago
• tml-epfl / adv-training-corruptions
  On the effectiveness of adversarial training against common corruptions [UAI 2022]
  ☆30Updated 2 years ago
• yaodongyu / Rethink-BiasVariance-Tradeoff
  Rethinking Bias-Variance Trade-off for Generalization of Neural Networks
  ☆49Updated 4 years ago
• andyzoujm / pixmix
  PixMix: Dreamlike Pictures Comprehensively Improve Safety Measures (CVPR 2022)
  ☆106Updated 2 years ago
• singlasahil14 / salient_imagenet
  Code for the ICLR 2022 paper. Salient Imagenet: How to discover spurious features in deep learning?
  ☆40Updated 2 years 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
• tml-epfl / sam-low-rank-features
  Sharpness-Aware Minimization Leads to Low-Rank Features [NeurIPS 2023]
  ☆28Updated last year
• tml-epfl / understanding-sam
  Towards Understanding Sharpness-Aware Minimization [ICML 2022]
  ☆35Updated 2 years ago
• justincui03 / dc_benchmark
  ☆86Updated 2 years ago
• JeanKaddour / WASAM
  Weight-Averaged Sharpness-Aware Minimization (NeurIPS 2022)
  ☆28Updated 2 years ago
• 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…
  ☆69Updated 2 years ago
• liuchen11 / AdversaryLossLandscape
  On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]
  ☆36Updated 3 years ago
• PolinaKirichenko / deep_feature_reweighting
  ☆107Updated last year
• facebookresearch / augmentation-corruption
  This repository provides code for "On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness".
  ☆45Updated 2 years ago
• RulinShao / on-the-adversarial-robustness-of-visual-transformer
  Code for the paper "On the Adversarial Robustness of Visual Transformers"
  ☆56Updated 3 years ago
• gatheluck / FourierHeatmap
  Unofficial pytorch implementation of Fourier Heat Map proposed in 'A Fourier Perspective on Model Robustness in Computer Vision' [Yin+, N…
  ☆74Updated last year
• tml-epfl / understanding-fast-adv-training
  Understanding and Improving Fast Adversarial Training [NeurIPS 2020]
  ☆95Updated 3 years ago
• davidstutz / confidence-calibrated-adversarial-training
  Implementation of Confidence-Calibrated Adversarial Training (CCAT).
  ☆45Updated 4 years ago
• Weixin-Liang / MetaShift
  MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts (ICLR 2022)
  ☆109Updated 2 years ago
• VITA-Group / Sparsity-Win-Robust-Generalization
  [ICLR 2022] "Sparsity Winning Twice: Better Robust Generalization from More Efficient Training" by Tianlong Chen*, Zhenyu Zhang*, Pengjun…
  ☆39Updated 3 years ago