Alternatives and similar repositories for pytorch-coteaching

Users that are interested in pytorch-coteaching are comparing it to the libraries listed below

• RyanWangZf / Influence_Subsampling
  Official Implementation of Unweighted Data Subsampling via Influence Function - AAAI 2020
  ☆64Updated 4 years ago
• mansheej / data_diet
  ☆109Updated 2 years ago
• orionw / Multilingual-Federated-Learning
  Code for the paper "Pretrained Models for Multilingual Federated Learning" at NAACL 2022
  ☆11Updated 3 years ago
• wzhouad / Contra-OOD
  Source code for paper "Contrastive Out-of-Distribution Detection for Pretrained Transformers", EMNLP 2021
  ☆40Updated 3 years ago
• Princeton-SysML / kNNLM_privacy
  Official implementation of Privacy Implications of Retrieval-Based Language Models (EMNLP 2023). https://arxiv.org/abs/2305.14888
  ☆36Updated last year
• rabeehk / hyperformer
  ☆158Updated 4 years ago
• BaeHeeSun / NPC
  ☆25Updated last year
• microsoft / MLC
  Meta Label Correction for Noisy Label Learning
  ☆86Updated 3 years ago
• AkariAsai / ATTEMPT
  This is the oficial repository for "Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft Prompts" (EMNLP 2022)
  ☆102Updated 2 years ago
• HazyResearch / thanos-code
  Code release for the paper Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive Learning
  ☆30Updated 3 years ago
• lancopku / FedMNMT
  [Findings of ACL 2023] Communication Efficient Federated Learning for Multilingual Machine Translation with Adapter
  ☆12Updated 2 years ago
• RenkunNi / MetaContrastive
  The official code for the publication: "The Close Relationship Between Contrastive Learning and Meta-Learning".
  ☆18Updated 3 years ago
• QingruZhang / PLATON
  This pytorch package implements PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance (ICML 2022).
  ☆46Updated 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…
  ☆54Updated 3 years ago
• fuzihaofzh / AnalyzeParameterEfficientFinetune
  On the Effectiveness of Parameter-Efficient Fine-Tuning
  ☆38Updated last year
• rabeehk / vibert
  Implementation for Variational Information Bottleneck for Effective Low-resource Fine-tuning, ICLR 2021
  ☆41Updated 4 years ago
• varunnair18 / FISH
  Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).
  ☆59Updated 3 years ago
• SALT-NLP / IDBR
  Codes for the paper: "Continual Learning for Text Classification with Information Disentanglement Based Regularization"
  ☆45Updated 2 years ago
• wutong8023 / PLM4CL
  ICLR 2022
  ☆18Updated 3 years ago
• joshr17 / IFM
  Code for paper "Can contrastive learning avoid shortcut solutions?" NeurIPS 2021.
  ☆47Updated 3 years ago
• acmi-lab / PU_learning
  Code and results accompanying our paper titled Mixture Proportion Estimation and PU Learning: A Modern Approach at Neurips 2021 (Spotligh…
  ☆44Updated last year
• schwartz-lab-NLP / papa
  Code for the PAPA paper
  ☆27Updated 2 years ago
• microsoft / Stochastic-Mixture-of-Experts
  This package implements THOR: Transformer with Stochastic Experts.
  ☆65Updated 4 years ago
• JetRunner / MetaDistil
  Code for ACL 2022 paper "BERT Learns to Teach: Knowledge Distillation with Meta Learning".
  ☆86Updated 3 years ago
• anshuman23 / InfDataSel
  Code for paper: “What Data Benefits My Classifier?” Enhancing Model Performance and Interpretability through Influence-Based Data Selecti…
  ☆24Updated last year
• anniesch / jtt
  Code for "Just Train Twice: Improving Group Robustness without Training Group Information"
  ☆72Updated last year
• Kaleidophon / nlp-uncertainty-zoo
  Model zoo for different kinds of uncertainty quantification methods used in Natural Language Processing, implemented in PyTorch.
  ☆53Updated 2 years ago
• kawine / dataset_difficulty
  "Understanding Dataset Difficulty with V-Usable Information" (ICML 2022, outstanding paper)
  ☆87Updated 2 years ago
• microsoft / UST
  Uncertainty-aware Self-training
  ☆121Updated last year
• cambridgeltl / autopeft
  AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-Tuning (Zhou et al.; TACL 2024)
  ☆47Updated last year