stanford-futuredata / selection-via-proxy

Related projects ⓘ

Alternatives and complementary repositories for selection-via-proxy

• UMBCvision / CompRess
  Compressing Representations for Self-Supervised Learning
  ☆78Updated 3 years ago
• RAIVNLab / supsup
  Code for "Supermasks in Superposition"
  ☆117Updated last year
• yaohungt / Barlow-Twins-HSIC
  ☆58Updated 2 years ago
• AlanChou / Truncated-Loss
  PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018
  ☆125Updated 5 years ago
• alinlab / Confident_classifier
  Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018
  ☆178Updated 4 years ago
• mansheej / data_diet
  ☆103Updated last year
• zeyademam / active_learning
  Code for Active Learning at The ImageNet Scale. This repository implements many popular active learning algorithms and allows training wi…
  ☆52Updated 2 years ago
• snu-mllab / Co-Mixup
  Official PyTorch implementation of "Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity" (ICLR'21 Oral)
  ☆104Updated 2 years ago
• haochenglouis / cores
  Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)
  ☆34Updated 3 years ago
• ContrastToDivide / C2D
  PyTorch implementation of "Contrast to Divide: self-supervised pre-training for learning with noisy labels"
  ☆70Updated 3 years ago
• gudovskiy / al-fk-self-supervision
  Official PyTorch code for CVPR 2020 paper "Deep Active Learning for Biased Datasets via Fisher Kernel Self-Supervision"
  ☆34Updated 3 years ago
• sinhasam / vaal
  Variational Adversarial Active Learning (ICCV 2019)
  ☆225Updated last year
• asappresearch / aum
  ☆80Updated last year
• Newbeeer / L_DMI
  Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"
  ☆117Updated last year
• gyhui14 / spottune
  SpotTune: Transfer Learning through Adaptive Fine-tuning
  ☆89Updated 5 years ago
• google-research / remixmatch
  ☆130Updated 2 years ago
• ozansener / active_learning_coreset
  Source code for ICLR 2018 Paper: Active Learning for Convolutional Neural Networks: A Core-Set Approach
  ☆260Updated 6 years ago
• hendrycks / error-detection
  A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
  ☆224Updated 5 years ago
• feidfoe / AdjustBnd4Imbalance
  Adjust Decision Boundary for Class Imbalanced Learning
  ☆18Updated 4 years ago
• megvii-research / FSSD_OoD_Detection
  [SafeAI'21] Feature Space Singularity for Out-of-Distribution Detection.
  ☆80Updated 3 years ago
• xingruiyu / coteaching_plus
  ICML'19 How does Disagreement Help Generalization against Label Corruption?
  ☆83Updated 5 years ago
• hankook / SLA
  Self-supervised Label Augmentation via Input Transformations (ICML 2020)
  ☆104Updated 3 years ago
• VectorInstitute / gram-ood-detection
  ☆46Updated 3 years ago
• JordanAsh / badge
  An implementation of the BADGE batch active learning algorithm.
  ☆198Updated 5 months ago
• alinlab / M2m
  Code for the paper "M2m: Imbalanced Classification via Major-to-minor Translation" (CVPR 2020)
  ☆94Updated 3 years ago
• seominseok0429 / label-smoothing-visualization-pytorch
  When Does Label Smoothing Help?_pytorch_implementationimp
  ☆124Updated 4 years ago
• mtoneva / example_forgetting
  ☆174Updated 3 months ago
• yukimasano / linear-probes
  Evaluating AlexNet features at various depths
  ☆39Updated 4 years ago
• jizongFox / pytorch-randaugment
  Unofficial PyTorch Reimplementation of AutoAugment and RandAugment.
  ☆36Updated 2 years ago