Alternatives and similar repositories for Mix-n-Match-Calibration

Users that are interested in Mix-n-Match-Calibration are comparing it to the libraries listed below

• izmailovpavel / spurious_feature_learning
  ☆45Updated 2 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
  ☆37Updated 4 years ago
• Newbeeer / TRM
  Learning Representations that Support Robust Transfer of Predictors
  ☆20Updated 3 years ago
• alexrame / fishr
  Official PyTorch implementation of the Fishr regularization for out-of-distribution generalization
  ☆86Updated 3 years ago
• arobey1 / mbdg
  ☆36Updated 3 years ago
• ryoungj / optdom
  [ICLR'22] Self-supervised learning optimally robust representations for domain shift.
  ☆24Updated 3 years ago
• IntelLabs / AVUC
  Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.
  ☆55Updated 2 years ago
• mpezeshki / Gradient_Starvation
  Gradient Starvation: A Learning Proclivity in Neural Networks
  ☆61Updated 4 years ago
• GT-RIPL / Geometric-Sensitivity-Decomposition
  ☆18Updated 3 years ago
• ahujak / IB-IRM
  ☆30Updated 3 years ago
• YannDubs / Invariant-Self-Supervised-Learning
  Pytorch code for "Improving Self-Supervised Learning by Characterizing Idealized Representations"
  ☆41Updated 2 years ago
• YyzHarry / SubpopBench
  [ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift
  ☆108Updated last year
• Jonathan-Pearce / calibration-toolbox
  NumPy library for calibration metrics
  ☆73Updated 3 months ago
• anniesch / jtt
  Code for "Just Train Twice: Improving Group Robustness without Training Group Information"
  ☆72Updated last year
• huaxiuyao / LISA
  LISA for ICML 2022
  ☆49Updated 2 years ago
• bat-sheva / Conformal-Learning
  ☆25Updated 3 years ago
• VirtuosoResearch / Regularized-Self-Labeling
  A regularized self-labeling approach to improve the generalization and robustness of fine-tuned models
  ☆28Updated 2 years ago
• mpagli / Agree-to-Disagree
  Repo for the paper: "Agree to Disagree: Diversity through Disagreement for Better Transferability"
  ☆36Updated 2 years ago
• deeplearning-wisc / gradnorm_ood
  On the Importance of Gradients for Detecting Distributional Shifts in the Wild
  ☆56Updated 2 years ago
• ondrejbohdal / meta-calibration
  Official PyTorch implementation of "Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error"
  ☆35Updated last year
• acmi-lab / RLSbench
  Code and results accompanying our paper titled RLSbench: Domain Adaptation under Relaxed Label Shift
  ☆34Updated last year
• stanford-futuredata / sinkhorn-label-allocation
  Sinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms. The SLA algorithm is described in fu…
  ☆53Updated 3 years ago
• TUM-DAML / dbu-robustness
  Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable ? (ICML 2021)
  ☆28Updated 2 years ago
• facebookresearch / BalancingGroups
  Simple data balancing baselines for worst-group-accuracy benchmarks.
  ☆42Updated last year
• belaalb / G2DM
  Generalizing to unseen domains via distribution matching
  ☆72Updated 4 years ago
• VectorInstitute / gram-ood-detection
  ☆46Updated 4 years ago
• AIgen / df-posthoc-calibration
  Model-agnostic posthoc calibration without distributional assumptions
  ☆42Updated last year
• AmirooR / IntraOrderPreservingCalibration
  ☆12Updated 2 years ago
• KaosEngineer / PriorNetworks-OLD
  ☆42Updated 6 years ago
• jfc43 / robust-ood-detection
  Robust Out-of-distribution Detection in Neural Networks
  ☆72Updated 3 years ago