Alternatives and similar repositories for nnPUSB

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

• ZaydH / arbitrary_pu
  NeurIPS'20 Paper: "Learning from Positive and Unlabeled Data with Arbitrary Positive Shift"
  ☆17Updated last year
• cimeister / pu-learning
  Pytorch implementation of risk estimators for unbiased and non-negative positive-unlabeled learning
  ☆87Updated 9 months ago
• VITA-Group / Self-PU
  [ICML2020] "Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training" by Xuxi Chen, Wuyang Chen, Tianlong Chen, Ye Yuan, Chen Gon…
  ☆68Updated 3 years ago
• cyber-meow / PUbiasedN
  PyTorch implementation for the paper Classification from Positive, Unlabeled and Biased Negative Data.
  ☆19Updated last year
• byeonghu-na / vae-pu
  Official Tensorflow implementation for Deep Generative Positive-Unlabeled Learning under Selection Bias (VAE-PU) in CIKM 2020.
  ☆12Updated 3 years ago
• weitongseu / PU-Learning
  This repo lists some researches and applications in PU learning.
  ☆12Updated 5 years ago
• huaxiuyao / GFL
  GFL for AAAI 2020
  ☆31Updated 4 years ago
• iQua / CVPR2020-Shoestring
  Official code for the CVPR 2020 paper "Shoestring: Graph-Based Semi-Supervised Classification with Severely Limited Labeled Data."
  ☆10Updated 4 years ago
• chauhanjatin10 / GraphsFewShot
  Few Shot Learning on Graphs
  ☆33Updated 2 years ago
• liulu112601 / Gated-Propagation-Net
  NeurIPS 2019 : Learning to Propagate for Graph Meta-Learning
  ☆36Updated 5 years ago
• vikasverma1077 / GraphMix
  Code for reproducing results in GraphMix paper
  ☆72Updated 2 years ago
• HC-Feynman / vpu
  A PyTorch implementation of the Variational approach for PU learning
  ☆29Updated 4 years ago
• vwz / AGE
  Active Learning for Graph Embedding
  ☆32Updated 8 years ago
• Kaixiong-Zhou / DGN
  Pytorch implementation of differentiable group normalization (NeurIPS 2020)
  ☆38Updated 4 years ago
• Luoyadan / BGNN-AAAI
  official PyTorch implementation of paper "Continual Meta-Learning with Bayesian Graph Neural Networks" (AAAI2020)
  ☆63Updated 4 years ago
• MasaKat0 / PUlearning
  Code for Positive-Unlabeled learning.
  ☆35Updated 2 years ago
• Ferenas / CAVL
  Exploiting Class Activation Value for Partial-Label Learning, ICLR 2022 (poster)
  ☆14Updated 3 years ago
• ahujak / IB-IRM
  ☆30Updated 3 years ago
• guixianjin / noisy_label_papers
  This repository is used to record current noisy label paper in mainstream ML and CV conference and journal.
  ☆35Updated 3 years ago
• nolfwin / symloss-ber-auc
  Code for the paper: On Symmetric Losses for Learning from Corrupted Labels
  ☆19Updated 6 years ago
• Luodian / IIB
  ☆16Updated 3 years ago
• a5507203 / Instance-dependent-Label-noise-Learning-under-a-Structural-Causal-Model
  ☆16Updated last year
• GarrettLee / nnpu_tf
  Code for reproducing experiments on MNIST and CIFAR-10 in paper "Positive-Unlabeled Learning with Non-Negative Risk Estimator".
  ☆21Updated 2 years ago
• guolz-ml / Survey-on-Robust-Semi-Supervised-Learning
  Survey on Robust Weakly Supervised Learning
  ☆13Updated 3 years ago
• TrustAGI-Lab / UDAGCN
  Python implementation of "Unsupervised Domain Adaptive Graph Convolutional Networks", WWW-20.
  ☆56Updated 4 years ago
• wwangwitsel / PARM
  [NeurIPS'20] Semi-Supervised Partial Label Learning via Confidence-Rated Margin Maximization
  ☆20Updated 3 years ago
• guangxinsuuu / Positive-and-Unlabeled-Learning-from-Imbalanced-Data
  Code for the paper named "Positive-Unlabeled Learning from Imbalanced Data" which has been accepted by IJCAI-21
  ☆16Updated 3 years ago
• Newbeeer / Max-MIG
  Code for ICLR 2019 Paper, "MAX-MIG: AN INFORMATION THEORETIC APPROACH FOR JOINT LEARNING FROM CROWDS"
  ☆25Updated 2 years ago
• takashiishida / comp
  [NeurIPS 2017] [ICML 2019] Code for complementary-label learning
  ☆48Updated last year
• huaxiuyao / ATS
  ATS for NeurIPS 2021
  ☆23Updated 3 years ago