Alternatives and similar repositories for Class-Imbalance

Users that are interested in Class-Imbalance are comparing it to the libraries listed below

• sclincha / xrce_msda_da_regularization
  Regularized marginalized Stacked Denoising Autoencoders for Domain Adaptation
  ☆12Updated 8 years ago
• titu1994 / LSTM-FCN-Ablation
  Repository for the ablation study of "Long Short-Term Memory Fully Convolutional Networks for Time Series Classification"
  ☆54Updated 6 years ago
• kevinlyu / Wasserstein-Adversarial-Domain-Adaptation
  Wasserstein Based Domain Adaptation Model
  ☆46Updated 6 years ago
• shubhamjn1 / Pseudo-Labelling---A-Semi-supervised-learning-technique
  ☆61Updated 7 years ago
• aniketde / DomainGeneralizationMarginal
  ☆15Updated 7 years ago
• pochih / MNIST-multitask
  6️⃣6️⃣6️⃣ Reproduce ICLR '18 under-reviewed paper "MULTI-TASK LEARNING ON MNIST IMAGE DATASETS"
  ☆42Updated 7 years ago
• jindongwang / tf-dann
  Domain-Adversarial Neural Network in Tensorflow
  ☆37Updated 6 years ago
• alimirzaei / adverserial-autoencoder-keras
  Keras Implementation of adverserial autoencoder (AAE)
  ☆56Updated 6 years ago
• raj-shah / BayesianCNN
  Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference, Gal et al. 2015
  ☆36Updated 7 years ago
• takeshi-teshima / few-shot-domain-adaptation-by-causal-mechanism-transfer
  Implementation of Few-shot Domain Adaptation by Causal Mechanism Transfer (ICML 2020)
  ☆42Updated 2 years ago
• michaal94 / Semisupervised-Clustering
  PyTorch semi-supervised clustering with Convolutional Autoencoders
  ☆24Updated 6 years ago
• bruno-31 / GAN-manifold-regularization
  This is the code for our paper: Semi-Supervised Learning With GANs: Revisiting Manifold Regularization (ICLR 2018)
  ☆44Updated 6 years ago
• nejlag / Semi-Supervised-Learning-GAN
  Semi-supervised Learning GAN
  ☆79Updated 7 years ago
• zhuxinqimac / B-CNN
  Sample code of B-CNN paper (https://arxiv.org/abs/1709.09890) written in Python3+.
  ☆55Updated 3 years ago
• Albertsr / Class-Imbalance
  Cost-Sensitive Learning / ReSampling / Weighting / Thresholding / BorderlineSMOTE / AdaCost / etc.
  ☆107Updated 4 years ago
• mollymr305 / mnist-mc-dropout
  model uncertainty using mc dropout
  ☆20Updated 6 years ago
• zxlzr / Deep-Transfer-Learning
  Deep Transfer Learning Papers
  ☆80Updated 3 years ago
• lethaiq / GRACE_KDD20
  GRACE: Generating Concise and Informative Contrastive Sample to Explain Neural Network Model’s Prediction. Thai Le, Suhang Wang, Dongwon …
  ☆21Updated 4 years ago
• winstonll / COPOD
  Supplementary material for ICDM 20 paper "COPOD: Copula-Based Outlier Detection"
  ☆60Updated 4 years ago
• XifengGuo / DEC-DA
  Deep Embedded Clustering with Data Augmentation (DEC-DA). Performance on MNIST (acc=0.985, nmi=0.960).
  ☆55Updated 6 years ago
• MadhumitaSushil / SDAE
  Stacked Denoising AutoEncoder
  ☆78Updated 5 years ago
• ljain2 / libsvm-openset
  ☆51Updated 10 years ago
• P1Analytics / Pseudo-Label-for-Deep-Neural-Networks
  Semi-Supervised Learning Method for Deep Neural Networks
  ☆28Updated 7 years ago
• ksalsw1996 / pytorch_DAE
  pytorch implementation of stacked denoising autoencoder
  ☆20Updated 7 years ago
• mabirck / adaptative-dropout-pytorch
  Pytorch implementation of Adaptative Dropout a.ka Standout.
  ☆12Updated 7 years ago
• hezhangsprinter / SROSR
  This is the implementation of 'Sparse Representation based Open-set Recognition (T-PAMI)
  ☆23Updated 8 years ago
• sumanth-bmsce / Deep-Neural-Network-for-Clustering
  Autoencoders - a deep neural network was used for feature extraction followed by clustering of the "Cancer" dataset using k-means techni…
  ☆13Updated 7 years ago
• vuptran / sesemi
  supervised and semi-supervised image classification with self-supervision (Keras)
  ☆45Updated 4 years ago
• v-mipeng / ClassImbalanceLearning
  This is the implementation code for the paper "Trainable Undersampling for Class-Imbalance Learning" published in AAAI2019
  ☆16Updated 6 years ago
• snehchav / Semi-Supervised-Image-Classification
  The code written on the understanding of the paper: "Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabel…
  ☆18Updated 7 years ago