Alternatives and similar repositories for ATS

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

• huaxiuyao / MLTI
  MLTI for ICLR 2022
  ☆30Updated 3 years ago
• huaxiuyao / MetaMix
  MetaMix for ICML 2021
  ☆27Updated 4 years ago
• huaxiuyao / GFL
  GFL for AAAI 2020
  ☆31Updated 4 years ago
• Wang-ML-Lab / GRDA
  [ICLR 2022] Graph-Relational Domain Adaptation
  ☆45Updated last year
• m-Just / OoD-Bench
  ☆44Updated 5 months ago
• mfederici / Multi-View-Information-Bottleneck
  Implementation of Multi-View Information Bottleneck
  ☆132Updated 5 years ago
• ynysjtu / ood_bench
  ☆49Updated 2 years ago
• Luodian / IIB
  ☆17Updated 3 years ago
• PanZiqiAI / disentangled-information-bottleneck
  ☆32Updated 4 years ago
• hehaodele / CIDA
  [ICML 2020] Continuously Indexed Domain Adaptation
  ☆119Updated 3 years ago
• x-zho14 / MAPLE
  Code for Model Agnostic Sample Reweighting for Out-of-Distribution Learning
  ☆44Updated 2 years ago
• LFhase / PAIR
  [ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization
  ☆52Updated last year
• Luoyadan / BGNN-AAAI
  official PyTorch implementation of paper "Continual Meta-Learning with Bayesian Graph Neural Networks" (AAAI2020)
  ☆63Updated 5 years ago
• WonderSeven / LSSAE
  The official implementation of paper "Generalizing to Evolving Domains with Latent Structure-Aware Sequential Autoencoder"
  ☆24Updated last year
• anshuln / Training-for-the-Future
  Official code release for the NeurIPS 2021 article Training for the Future: A Simple Gradient Interpolation Loss to Generalize Along Time…
  ☆10Updated 3 years ago
• jiangmengli / metaug
  ☆18Updated 2 years ago
• kaize0409 / Meta-PN
  PyTorch Implementation for "Meta Propagation Networks for Graph Few-shot Semi-supervised Learning" (AAAI2022)
  ☆29Updated 3 years ago
• linyongver / Bayesian-Invariant-Risk-Minmization
  This is the code for the paper Bayesian Invariant Risk Minmization of CVPR 2022.
  ☆46Updated 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 4 years ago
• LiqunChen0606 / Graph-Optimal-Transport
  Code for ICML 2020 "Graph Optimal Transport for Cross-Domain Alignment"
  ☆158Updated 5 years ago
• xiaoboxia / CDR
  ICLR‘2021: Robust Early-learning: Hindering the Memorization of Noisy Labels
  ☆77Updated 4 years ago
• lvjiaqi77 / PRODEN
  Code for the paper "Progressive Identification of True Labels for Partial-Label Learning".
  ☆52Updated 5 years ago
• Luodian / Learning-Invariant-Representations-and-Risks
  Pytorch code release of CVPR 21 Paper: Learning Invariant Representations and Risks
  ☆31Updated 4 years ago
• Wang-ML-Lab / VDI
  [ICLR 2023 (Spotlight)] Domain-Indexing Variational Bayes: Interpretable Domain Index for Domain Adaptation
  ☆39Updated last year
• chauhanjatin10 / GraphsFewShot
  Few Shot Learning on Graphs
  ☆33Updated 2 years ago
• hlzhang109 / DDG
  [CVPR 2022 Oral] Towards Principled Disentanglement for Domain Generalization
  ☆63Updated 2 years ago
• liyiying / Feature_Critic
  Feature-Critic Networks for Heterogeneous Domain Generalisation
  ☆53Updated 6 years ago
• changliu00 / causal-semantic-generative-model
  Codes for Causal Semantic Generative model (CSG), the model proposed in "Learning Causal Semantic Representation for Out-of-Distribution …
  ☆74Updated 3 years ago
• kakaoenterprise / Learning-Debiased-Disentangled
  Official Pytorch implementation of "Learning Debiased Representation via Disentangled Feature Augmentation (Neurips 2021, Oral)"
  ☆103Updated 2 years ago
• Ferenas / CAVL
  Exploiting Class Activation Value for Partial-Label Learning, ICLR 2022 (poster)
  ☆14Updated 3 years ago