Alternatives and similar repositories for causal-bald

Users that are interested in causal-bald are comparing it to the libraries listed below

• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆83Updated last year
• OATML / ucate
  Uncertainty in Conditional Average Treatment Effect Estimation
  ☆33Updated 4 years ago
• aangelopoulos / rcps
  Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"
  ☆87Updated last year
• nke001 / causal_learning_unknown_interventions
  Code for "Neural causal learning from unknown interventions"
  ☆104Updated 5 years ago
• diviyank / SAM
  Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)
  ☆54Updated 4 years ago
• charmlab / recourse
  Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831
  ☆37Updated 2 years ago
• IliasZadik / double_orthogonal_ml
  ☆11Updated 7 years ago
• bradyneal / realcause
  Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…
  ☆83Updated 4 years ago
• csquires / causal-rep-learning-reading-group
  ☆22Updated 2 years ago
• aangelopoulos / ltt
  Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control
  ☆71Updated last year
• mrojascarulla / causal_transfer_learning
  ☆32Updated 7 years ago
• anndvision / quince
  Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding
  ☆23Updated 3 years ago
• dtak / ocbnn-public
  General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.
  ☆38Updated 3 years ago
• microsoft / bayesianize
  Bayesianize: A Bayesian neural network wrapper in pytorch
  ☆90Updated last year
• adrianjav / heterogeneous_vaes
  Pytorch implementation of VAEs for heterogeneous likelihoods.
  ☆43Updated 3 years ago
• debmandal / causality-fairness
  References for Papers at the Intersection of Causality and Fairness
  ☆18Updated 7 years ago
• mingzhang-yin / CoCo
  An optimization-based algorithm to accurately estimate the causal effects and robustly predict under distribution shifts. It leverages th…
  ☆14Updated last year
• sjblim / rmsn_nips_2018
  ☆40Updated 6 years ago
• trevorcampbell / bayesian-coresets
  Automated Scalable Bayesian Inference
  ☆131Updated 3 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆58Updated 4 years ago
• ae-foster / dad
  Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
  ☆38Updated 4 years ago
• vdorie / npci
  Non-parametrics for Causal Inference
  ☆50Updated 3 years ago
• oxcsml / ML_bazaar
  OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.
  ☆94Updated 4 years ago
• JonathanWenger / pycalib
  Non-Parametric Calibration for Classification (AISTATS 2020)
  ☆19Updated 3 years ago
• d909b / cxplain
  Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
  ☆132Updated 5 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆85Updated 5 years ago
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 4 years ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆90Updated 5 years ago
• MFreidank / pysgmcmc
  Bayesian Deep Learning with Stochastic Gradient MCMC Methods
  ☆38Updated 4 years ago
• juangamella / aicp
  Code to reproduce the experimental results from the paper "Active Invariant Causal Prediction: Experiment Selection Through Stability", b…
  ☆21Updated 2 years ago