Alternatives and similar repositories for Instance-dependent-Label-noise-Learning-under-a-Structural-Causal-Model

Users that are interested in Instance-dependent-Label-noise-Learning-under-a-Structural-Causal-Model are comparing it to the libraries listed below

• Ferenas / CAVL
  Exploiting Class Activation Value for Partial-Label Learning, ICLR 2022 (poster)
  ☆14Updated 3 years ago
• Hao-Ning / MEIDTM-Instance-Dependent-Label-Noise-Learning-with-Manifold-Regularized-Transition-Matrix-Estimatio
  pytorch
  ☆10Updated 3 years ago
• a5507203 / dual-t-reducing-estimation-error-for-transition-matrix-in-label-noise-learning
  ☆15Updated last year
• xiaoboxia / CDR
  ICLR‘2021: Robust Early-learning: Hindering the Memorization of Noisy Labels
  ☆76Updated 4 years ago
• hbzju / SoLar
  Source code for NeurIPS 2022 paper SoLar
  ☆29Updated last year
• chenpf1025 / IDN
  AAAI 2021: Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise
  ☆35Updated 4 years ago
• ShiYunyi / Meta-Weight-Net_Code-Optimization
  A new code framework that uses pytorch to implement meta-learning, and takes Meta-Weight-Net as an example.
  ☆60Updated 3 years ago
• jkatzsam / woods_ood
  ☆16Updated 3 years ago
• x-zho14 / MAPLE
  Code for Model Agnostic Sample Reweighting for Out-of-Distribution Learning
  ☆44Updated 2 years ago
• xuefeng-li1 / Provably-end-to-end-label-noise-learning-without-anchor-points
  ☆12Updated 4 years ago
• tmllab / 2021_ICCV_Me-Momentum
  ☆14Updated 2 years ago
• m-Just / OoD-Bench
  ☆44Updated 2 months ago
• UCSC-REAL / cores
  Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)
  ☆37Updated 4 years ago
• Kthyeon / FINE_official
  NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"
  ☆39Updated 3 years ago
• hongxin001 / open-sampling
  Official code for ICML 2022: Open-Sampling: Exploring Out-of-Distribution Data for Re-balancing Long-tailed Datasets
  ☆15Updated 2 years ago
• palm-ml / valen
  Instance-Dependent Partial Label Learning（NIPS'21）；Variational Label Enhancement for Instance-Dependent Partial Label Learning（TPAMI）
  ☆25Updated 3 weeks ago
• lijichang / LNL-NCE
  A pytorch implementation for "Neighborhood Collective Estimation for Noisy Label Identification and Correction", which is accepted by ECC…
  ☆25Updated 2 years ago
• mndu / RNF-Fairness
  PyTorch code for the Neurips 2021 paper: Fairness via Representation Neutralization
  ☆10Updated 3 years ago
• DandanGuo1993 / reweight-imbalance-classification-with-OT
  ☆13Updated 2 years ago
• ShuoYang-1998 / BLTM
  [ICML'2022] Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network
  ☆19Updated 2 years ago
• deeplearning-wisc / vit-spurious-robustness
  ☆26Updated 2 years ago
• Vanint / Core-tuning
  This repository is the official implementation of Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regulari…
  ☆21Updated 2 years ago
• xiaoboxia / Part-dependent-label-noise
  NeurIPS'2020: Part-dependent Label Noise: Towards Instance-dependent Label Noise
  ☆60Updated 4 years ago
• QizhouWang / DOE
  ☆26Updated 2 years ago
• RenkunNi / MetaContrastive
  The official code for the publication: "The Close Relationship Between Contrastive Learning and Meta-Learning".
  ☆18Updated 2 years ago
• salesforce / RRL
  ☆17Updated last month
• linyongver / Bayesian-Invariant-Risk-Minmization
  This is the code for the paper Bayesian Invariant Risk Minmization of CVPR 2022.
  ☆44Updated 2 years ago
• tmllab / 2021_NeurIPS_PES
  ☆29Updated 2 years ago
• deeplearning-wisc / opencon
  Code for TMLR 2023 paper "OpenCon: Open-world Contrastive Learning"
  ☆37Updated 2 years ago
• pandeydeep9 / EvidentialResearch2023
  Analysis of evidential models
  ☆13Updated 2 years ago