Alternatives and similar repositories for TA-VAAL

Users that are interested in TA-VAAL are comparing it to the libraries listed below

• johnsk95 / PT4AL
  Official PyTorch implementation of "PT4AL: Using Self-Supervised Pretext Tasks for Active Learning (ECCV2022)"
  ☆54Updated last year
• Beichen1996 / SRAAL
  State-Relabeling Adversarial Active Learning
  ☆13Updated 3 years ago
• avihu111 / TypiClust
  Active Learning on a Budget - Opposite Strategies Suit High and Low Budgets
  ☆93Updated 7 months ago
• Javadzb / Class-Balanced-AL
  ☆22Updated 3 years ago
• virajprabhu / CLUE
  PyTorch code for Active Domain Adaptation via Clustering Uncertainty-weighted Embeddings (ICCV 2021)
  ☆44Updated last year
• siyuhuang / TOD
  PyTorch Implementation of Temporal Output Discrepancy for Active Learning, ICCV 2021
  ☆41Updated 2 years ago
• PrateekMunjal / TorchAL
  Official implementation of our paper: Towards Robust and Reproducible Active Learning using Neural Networks, accepted at CVPR 2022.
  ☆67Updated last year
• deeplearning-wisc / gradnorm_ood
  On the Importance of Gradients for Detecting Distributional Shifts in the Wild
  ☆56Updated 2 years ago
• Mattdl / RehearsalRevealed
  Official codebase of the "Rehearsal revealed:The limits and merits of revisiting samples in continual learning" paper.
  ☆27Updated 3 years ago
• RUC-DWBI-ML / CCAL
  This is the code of paper ``Contrastive Coding for Active Learning under Class Distribution Mismatch'' with python.
  ☆28Updated 2 years ago
• acl21 / deep-active-learning-pytorch
  A PyTorch toolkit with 8 popular deep active learning query methods implemented.
  ☆87Updated 3 years ago
• daintlab / confidence-aware-learning
  Confidence-Aware Learning for Deep Neural Networks (ICML2020)
  ☆74Updated 4 years ago
• chaht01 / Co2L
  Co^2L: Contrastive Continual Learning (ICCV2021)
  ☆96Updated 3 years ago
• khanrc / miro
  Official PyTorch implementation of MIRO (ECCV 2022)
  ☆87Updated 2 years ago
• thuml / Transferable-Query-Selection
  Code Release for "Transferable Query Selection for Active Domain Adaptation"(CVPR2021)
  ☆24Updated 3 years ago
• VITA-Group / SDCLR
  [ICML 2021] “ Self-Damaging Contrastive Learning”, Ziyu Jiang, Tianlong Chen, Bobak Mortazavi, Zhangyang Wang
  ☆63Updated 3 years ago
• asrafulashiq / transfer_broad
  Pytorch Code for "A Broad Study on the Transferability of Visual Representations with Contrastive Learning" (ICCV 2021)
  ☆36Updated 3 years ago
• bbuing9 / DARP
  Code for the paper "Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning" (NeurIPS 20)
  ☆73Updated 2 years ago
• bethgelab / robustness
  Robustness and adaptation of ImageNet scale models. Pre-Release, stay tuned for updates.
  ☆136Updated last year
• deeplearning-wisc / large_scale_ood
  MOS: Towards Scaling Out-of-distribution Detection for Large Semantic Space
  ☆91Updated 3 years ago
• LeeHyuck / ABC
  pytorch implementation of ABC : Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised Learning
  ☆37Updated 6 months ago
• VisionLearningGroup / OP_Match
  ☆58Updated 2 years ago
• divyam3897 / UCL
  Code for the paper "Representational Continuity for Unsupervised Continual Learning" (ICLR 22)
  ☆96Updated 2 years ago
• AminParvaneh / alpha_mix_active_learning
  The official implementation of Active Learning by Feature Mixing (ALFA-Mix) paper
  ☆84Updated 2 years ago
• rajatkoner08 / oodformer
  This is a code repository for paper OODformer: Out-Of-Distribution Detection Transformer
  ☆40Updated 3 years ago
• thuml / CoTuning
  Code release for NeurIPS 2020 paper "Co-Tuning for Transfer Learning"
  ☆40Updated 3 years ago
• yanbeic / ssl-class-mismatch
  Tensorflow Implementation on Paper [AAAI2020]Semi-Supervised Learning under Class Distribution Mismatch
  ☆15Updated 4 years ago
• VisionLearningGroup / visda21-dev
  ☆46Updated 3 years ago
• JordanAsh / badge
  An implementation of the BADGE batch active learning algorithm.
  ☆205Updated last year
• ContrastToDivide / C2D
  PyTorch implementation of "Contrast to Divide: self-supervised pre-training for learning with noisy labels"
  ☆71Updated 4 years ago