Alternatives and similar repositories for pycalib

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

• namkoong-lab / robustopt
  ☆43Updated 7 years ago
• mrojascarulla / causal_transfer_learning
  ☆32Updated 7 years ago
• AIgen / df-posthoc-calibration
  Model-agnostic posthoc calibration without distributional assumptions
  ☆42Updated 2 years ago
• uu-sml / calibration
  Python package for evaluating model calibration in classification
  ☆20Updated 6 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆83Updated last year
• k9k2 / qSGD
  SGD and Ordered SGD codes for deep learning, SVM, and logistic regression
  ☆36Updated 5 years ago
• Srceh / DistCal
  Code for the ICML 2019 paper: Distribution Calibration for Regression
  ☆22Updated 2 years ago
• p-lambda / verified_calibration
  Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…
  ☆152Updated 3 years ago
• OATML / causal-bald
  ☆18Updated 2 years ago
• dtak / ocbnn-public
  General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.
  ☆39Updated 3 years ago
• lsgos / uncertainty-adversarial-paper
  Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'
  ☆62Updated 7 years ago
• RuntianZ / doro
  Distributional and Outlier Robust Optimization (ICML 2021)
  ☆28Updated 4 years ago
• facebookresearch / InvarianceUnitTests
  Toy datasets to evaluate algorithms for domain generalization and invariance learning.
  ☆43Updated 4 years ago
• AMLab-Amsterdam / FNP
  Implementation of the Functional Neural Process models
  ☆42Updated 5 years ago
• wiseodd / last_layer_laplace
  Last-layer Laplace approximation code examples
  ☆83Updated 4 years ago
• facebookresearch / BalancingGroups
  Simple data balancing baselines for worst-group-accuracy benchmarks.
  ☆43Updated 2 years ago
• nke001 / causal_learning_unknown_interventions
  Code for "Neural causal learning from unknown interventions"
  ☆104Updated 5 years ago
• mblondel / smooth-ot
  Python implementation of smooth optimal transport.
  ☆61Updated 4 years ago
• brain-research / ncp
  Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
  ☆62Updated 5 years ago
• reiinakano / invariant-risk-minimization
  Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893
  ☆91Updated 5 years ago
• icml-mcbn / mcbn
  ☆53Updated 7 years ago
• Piyushi-0 / ACE
  Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.
  ☆51Updated 4 years ago
• team-approx-bayes / fromp
  Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"
  ☆44Updated 5 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• capybaralet / REx_code_release
  ☆63Updated 5 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 6 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆42Updated 3 years ago
• fengliu90 / DK-for-TST
  This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).
  ☆53Updated 4 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆86Updated 5 years ago
• ebonilla / gaussianprocesses
  Modern Gaussian Processes: Scalable Inference and Novel Applications
  ☆20Updated 6 years ago