Alternatives and similar repositories for valen

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

• lvjiaqi77 / PRODEN
  Code for the paper "Progressive Identification of True Labels for Partial-Label Learning".
  ☆52Updated 4 years ago
• hbzju / SoLar
  Source code for NeurIPS 2022 paper SoLar
  ☆29Updated last year
• hongwei-wen / LW-loss-for-partial-label
  ☆24Updated 3 years ago
• wu-dd / Advances-in-Partial-and-Complementary-Label-Learning
  A curated list of most recent papers & codes in Learning with Partial/Complementary Labels
  ☆61Updated 8 months ago
• hbzju / PiCO
  PyTorch implementation of PiCO https://arxiv.org/abs/2201.08984
  ☆218Updated last year
• xiemk / awesome-weakly-supervised-multi-label-learning
  ☆61Updated last year
• Ferenas / CAVL
  Exploiting Class Activation Value for Partial-Label Learning, ICLR 2022 (poster)
  ☆14Updated 3 years ago
• bhanML / label-noise-papers
  An update-to-date list for papers related with label-noise representation learning is here.
  ☆90Updated 3 years ago
• xiaoboxia / CDR
  ICLR‘2021: Robust Early-learning: Hindering the Memorization of Noisy Labels
  ☆77Updated 4 years ago
• ShikunLi / Sel-CL
  CVPR 2022: Selective-Supervised Contrastive Learning with Noisy Labels
  ☆93Updated 3 years ago
• Hao-Ning / MEIDTM-Instance-Dependent-Label-Noise-Learning-with-Manifold-Regularized-Transition-Matrix-Estimatio
  pytorch
  ☆10Updated 3 years ago
• microsoft / MLC
  Meta Label Correction for Noisy Label Learning
  ☆85Updated 2 years ago
• a5507203 / Instance-dependent-Label-noise-Learning-under-a-Structural-Causal-Model
  ☆16Updated last year
• guixianjin / noisy_label_papers
  This repository is used to record current noisy label paper in mainstream ML and CV conference and journal.
  ☆36Updated 3 years ago
• huaxiuyao / MetaMix
  MetaMix for ICML 2021
  ☆27Updated 4 years ago
• UCSC-REAL / cores
  Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)
  ☆38Updated 4 years ago
• WuYichen-97 / Learning-to-Purify-Noisy-Labels-via-Meta-Soft-Label-Corrector
  [AAAI 21] Utilizing meta-learning to correct the noisy labels.
  ☆15Updated 4 years ago
• hamanhbui / mDSDI
  Exploiting Domain-Specific Features to Enhance Domain Generalization (NeurIPS 2021).
  ☆28Updated 3 years ago
• LTH14 / targeted-supcon
  A PyTorch implementation of the paper Targeted Supervised Contrastive Learning for Long-tailed Recognition
  ☆102Updated last year
• salesforce / RRL
  ☆17Updated 3 months ago
• xiemk / SPML-LAC
  ☆16Updated 2 years ago
• guolz-ml / Survey-on-Robust-Semi-Supervised-Learning
  Survey on Robust Weakly Supervised Learning
  ☆13Updated 3 years ago
• changwxx / UniOT-for-UniDA
  Source code for the NeurIPS 2022 Spotlight paper: "Unified Optimal Transport Framework for Universal Domain Adaptation"
  ☆60Updated 2 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.
  ☆61Updated 3 years ago
• ailearn-ml / FLEM
  Code for "Fusion Label Enhancement for Multi-Label Learning" in IJCAI-ECAI 2022.
  ☆10Updated 2 years ago
• chenpf1025 / IDN
  AAAI 2021: Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise
  ☆35Updated 4 years ago
• huaxiuyao / ATS
  ATS for NeurIPS 2021
  ☆23Updated 3 years ago
• mfederici / Multi-View-Information-Bottleneck
  Implementation of Multi-View Information Bottleneck
  ☆131Updated 5 years ago
• wwangwitsel / PARM
  [NeurIPS'20] Semi-Supervised Partial Label Learning via Confidence-Rated Margin Maximization
  ☆21Updated 3 years ago
• Kthyeon / FINE_official
  NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"
  ☆39Updated 3 years ago