Alternatives and similar repositories for confident-sinkhorn-allocation

Users that are interested in confident-sinkhorn-allocation are comparing it to the libraries listed below

• cure-lab / deep-active-learning
  An implementation of the state-of-the-art Deep Active Learning algorithms
  ☆106Updated 2 years ago
• ucr-optml / AutoBalance
  ☆16Updated 4 years ago
• omegafragger / DDU
  Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty
  ☆145Updated 2 years ago
• avihu111 / TypiClust
  Active Learning on a Budget - Opposite Strategies Suit High and Low Budgets
  ☆100Updated last year
• frank-xwang / debiased-pseudo-labeling
  [CVPR 2022] Pytorch implementation for “Debiased Learning from Naturally Imbalanced Pseudo-Labels”
  ☆104Updated 3 months ago
• amazon-science / long-tailed-ood-detection
  Official implementation for "Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition" (I…
  ☆42Updated 2 years ago
• mingkai-zheng / WCL
  Weakly Supervised Contrastive Learning
  ☆44Updated 4 years ago
• pietroastolfi / suave-daino
  Code release for "Semi-supervised learning made simple with self-supervised clustering"
  ☆60Updated 2 years ago
• roysubhankar / uncertainty-sfda
  PyTorch code for Uncertainty-guided Source-free Domain Adaptation
  ☆35Updated 3 years ago
• alexrame / fishr
  Official PyTorch implementation of the Fishr regularization for out-of-distribution generalization
  ☆89Updated 3 years ago
• giannifranchi / LP_BNN
  This repository contains an official implementation of LPBNN.
  ☆38Updated 2 years ago
• huaxiuyao / C-Mixup
  C-Mixup for NeurIPS 2022
  ☆73Updated 2 years ago
• huaxiuyao / MetaMix
  MetaMix for ICML 2021
  ☆27Updated 4 years ago
• acmi-lab / Open-Set-Label-Shift
  Code and results accompanying our paper titled Domain Adaptation under Open Set Label Shift
  ☆32Updated 3 years ago
• mdca-loss / MDCA-Calibration
  [CVPR 2022] Official code for the paper: "A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved Neural Network Calibra…
  ☆33Updated 3 years ago
• BlackHC / batchbald_redux
  Reusable BatchBALD implementation
  ☆79Updated last year
• khainb / Mini-batch-OT
  A new mini-batch framework for optimal transport in deep generative models, deep domain adaptation, approximate Bayesian computation, col…
  ☆36Updated 2 years ago
• chingyaoc / InfoOT
  [ICML2023] InfoOT: Information Maximizing Optimal Transport
  ☆42Updated 2 years ago
• val-iisc / SDAT
  [ICML 2022]Source code for "A Closer Look at Smoothness in Domain Adversarial Training",
  ☆72Updated last year
• deeplearning-wisc / multi-label-ood
  ☆46Updated 4 years ago
• acmi-lab / RLSbench
  Code and results accompanying our paper titled RLSbench: Domain Adaptation under Relaxed Label Shift
  ☆35Updated 2 years ago
• hsouri / BayesianTransferLearning
  ☆111Updated 3 years ago
• MinaGhadimiAtigh / Hyperbolic-Busemann-Learning
  Hyperbolic Busemann Learning with Ideal Prototypes, NeurIPS2021
  ☆24Updated 4 years ago
• microsoft / Domain-Adaptation-with-Conditional-Distribution-Matching-and-Generalized-Label-Shift
  Code for the paper Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift
  ☆39Updated 5 years ago
• acl21 / deep-active-learning-pytorch
  A PyTorch toolkit with 8 popular deep active learning query methods implemented.
  ☆89Updated 4 years ago
• val-iisc / Saddle-LongTail
  [NeurIPS 2022] Source code for our paper "Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data"
  ☆24Updated 2 years ago
• teddykoker / evidential-learning-pytorch
  Evidential Deep Learning in PyTorch
  ☆68Updated 3 years ago
• kilianFatras / JUMBOT
  Official Python3 implementation of our ICML 2021 paper "Unbalanced minibatch Optimal Transport; applications to Domain Adaptation"
  ☆47Updated 3 years ago
• PrateekMunjal / TorchAL
  Official implementation of our paper: Towards Robust and Reproducible Active Learning using Neural Networks, accepted at CVPR 2022.
  ☆68Updated 2 years ago
• hongxin001 / open-sampling
  Official code for ICML 2022: Open-Sampling: Exploring Out-of-Distribution Data for Re-balancing Long-tailed Datasets
  ☆15Updated 3 years ago