Alternatives and similar repositories for df-posthoc-calibration

Users that are interested in df-posthoc-calibration are comparing it to the libraries listed below

• p-lambda / verified_calibration
  Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…
  ☆151Updated 2 years ago
• aangelopoulos / conformal-risk
  Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…
  ☆70Updated 2 years ago
• BlackHC / batchbald_redux
  Reusable BatchBALD implementation
  ☆79Updated last year
• geifmany / uncertainty_ICLR
  Code for the paper "Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers" published in ICLR 2019
  ☆14Updated 6 years ago
• sharpenb / Posterior-Network
  Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)
  ☆78Updated 3 years ago
• aangelopoulos / ltt
  Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control
  ☆70Updated 11 months ago
• JonathanWenger / pycalib
  Non-Parametric Calibration for Classification (AISTATS 2020)
  ☆19Updated 3 years ago
• zhang64-llnl / Mix-n-Match-Calibration
  ☆38Updated 4 years ago
• jlko / active-testing
  Active and Sample-Efficient Model Evaluation
  ☆24Updated 5 months ago
• torrvision / focal_calibration
  Code for the paper "Calibrating Deep Neural Networks using Focal Loss"
  ☆161Updated last year
• microsoft / bayesianize
  Bayesianize: A Bayesian neural network wrapper in pytorch
  ☆89Updated last year
• hsouri / BayesianTransferLearning
  ☆109Updated 3 years ago
• wiseodd / last_layer_laplace
  Last-layer Laplace approximation code examples
  ☆84Updated 4 years ago
• iancovert / fastshap
  An amortized approach for calculating local Shapley value explanations
  ☆102Updated last year
• Sanaelotfi / Bayesian_model_comparison
  Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".
  ☆36Updated 3 years ago
• mlfoundations / tableshift
  A benchmark for distribution shift in tabular data
  ☆56Updated last year
• cambridge-mlg / CLUE
  Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"
  ☆36Updated last year
• mertyg / beyond-confidence-atypicality
  Repository for the NeurIPS 2023 paper "Beyond Confidence: Reliable Models Should Also Consider Atypicality"
  ☆13Updated last year
• AmrMKayid / nam
  Neural Additive Models (Google Research)
  ☆73Updated 4 years ago
• MJ10 / DEUP
  Code for experiments to learn uncertainty
  ☆30Updated 2 years ago
• fel-thomas / Sobol-Attribution-Method
  👋 Code for the paper: "Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis" (NeurIPS 2021)
  ☆30Updated 3 years ago
• wiseodd / lula
  Companion code for the paper "Learnable Uncertainty under Laplace Approximations" (UAI 2021).
  ☆20Updated 4 years ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 3 years ago
• mrojascarulla / causal_transfer_learning
  ☆32Updated 7 years ago
• dtak / ocbnn-public
  General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.
  ☆38Updated 3 years ago
• HazyResearch / hidden-stratification
  Combating hidden stratification with GEORGE
  ☆64Updated 4 years ago
• Jonathan-Pearce / calibration-toolbox
  NumPy library for calibration metrics
  ☆73Updated 3 weeks ago
• ykwon0407 / beta_shapley
  Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)
  ☆41Updated 2 years ago
• hollance / reliability-diagrams
  Reliability diagrams visualize whether a classifier model needs calibration
  ☆158Updated 3 years ago
• kartikgupta-at-anu / spline-calibration
  Code implementation of our ICLR'21 paper "Calibration of Neural Networks using Splines"
  ☆22Updated 2 years ago