Alternatives and similar repositories for dwmil:

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

• jasonyanglu / ACDWM
  ACDWM (Adaptive Chunk-based Dynamic Weighted Majority)
  ☆10Updated 5 years ago
• natalialmg / MMPF
  Implementation of Minimax Pareto Fairness framework
  ☆21Updated 4 years ago
• ahujak / IB-IRM
  ☆30Updated 3 years ago
• ninghaohello / Interpretation2Adversary
  Adversarial learning by utilizing model interpretation
  ☆10Updated 6 years ago
• Haoang97 / TOHAN
  Source code for NeurIPS 2021 paper "TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation".
  ☆9Updated 2 years ago
• optimass / Maximally_Interfered_Retrieval
  Codebase for "Online Continual Learning with Maximally Interfered Retrieval"
  ☆101Updated 2 years ago
• bhanML / SIGUA
  ICML'20: SIGUA: Forgetting May Make Learning with Noisy Labels More Robust
  ☆15Updated 4 years ago
• kohpangwei / group-influence-release
  ☆50Updated 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.
  ☆59Updated 3 years ago
• jjbrophy47 / dare_rf
  Machine Unlearning for Random Forests
  ☆19Updated 10 months ago
• RyanWangZf / Influence_Subsampling
  Official Implementation of Unweighted Data Subsampling via Influence Function - AAAI 2020
  ☆65Updated 4 years ago
• lvjiaqi77 / PRODEN
  Code for the paper "Progressive Identification of True Labels for Partial-Label Learning".
  ☆49Updated 4 years ago
• UCSC-REAL / cores
  Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)
  ☆36Updated 4 years ago
• amiratag / DistributionalShapley
  Distributional Shapley: A Distributional Framework for Data Valuation
  ☆30Updated 11 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
• ecreager / eiil
  Code for Environment Inference for Invariant Learning (ICML 2021 Paper)
  ☆50Updated 3 years ago
• x-zho14 / MAPLE
  Code for Model Agnostic Sample Reweighting for Out-of-Distribution Learning
  ☆44Updated 2 years ago
• aviralkumar2907 / MMCE
  ☆19Updated 6 years ago
• p-lambda / gradual_domain_adaptation
  ☆37Updated 4 years ago
• ybjiaang / ACTIR
  Code repository for the paper "Invariant and Transportable Representations for Anti-Causal Domain Shifts"
  ☆16Updated 2 years ago
• charlesjin / adversarial_regularization
  A method based on manifold regularization for training adversarially robust neural networks
  ☆9Updated 5 years ago
• pokaxpoka / RoGNoisyLabel
  Description Code for the paper "Robust Inference via Generative Classifiers for Handling Noisy Labels".
  ☆32Updated 5 years ago
• Sunarker / Safeguarded-Dynamic-Label-Regression-for-Noisy-Supervision
  ☆9Updated last year
• changliu00 / causal-semantic-generative-model
  Codes for Causal Semantic Generative model (CSG), the model proposed in "Learning Causal Semantic Representation for Out-of-Distribution …
  ☆73Updated 3 years ago
• litian96 / TERM
  Tilted Empirical Risk Minimization (ICLR '21)
  ☆59Updated last year
• antoninbrthn / CSIDN
  Code for the article "Confidence Scores Make Instance-dependent Label-noise Learning Possible", ICML'21
  ☆9Updated 8 months ago
• IandRover / MAML_noisy_contrasive_learner
  ☆17Updated 2 years ago
• Angie-Liu / labelshift
  Regularized Learning under label shifts
  ☆18Updated 5 years ago
• linyongver / Bayesian-Invariant-Risk-Minmization
  This is the code for the paper Bayesian Invariant Risk Minmization of CVPR 2022.
  ☆44Updated last year
• Newbeeer / Max-MIG
  Code for ICLR 2019 Paper, "MAX-MIG: AN INFORMATION THEORETIC APPROACH FOR JOINT LEARNING FROM CROWDS"
  ☆25Updated last year