Alternatives and similar repositories for causal-falsify

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

• AlxndrMlk / blogs-code
  Code for blog posts.
  ☆20Updated 2 years ago
• tblume1992 / ConformalImpact
  Causal Impact but with MFLES and conformal prediction intervals
  ☆33Updated 10 months ago
• almost-matching-exactly / DAME-FLAME-Python-Package
  A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data
  ☆62Updated 3 months ago
• max-little / GRAPL
  GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference
  ☆83Updated 10 months ago
• StochasticTree / stochtree
  Stochastic tree ensembles (BART / XBART) for supervised learning and causal inference
  ☆59Updated last week
• soda-inria / survival-analysis-benchmark
  Exploratory repository to study predictive survival analysis models
  ☆38Updated 2 years ago
• profitopsai / ProRCA
  ☆21Updated 7 months ago
• Quantco / metalearners
  MetaLearners for CATE estimation
  ☆49Updated last week
• koaning / scikit-partial
  Pipeline components that support partial_fit.
  ☆46Updated last year
• FlorianWilhelm / bhm-at-scale
  🪜 Bayesian Hierarchical Models at Scale
  ☆51Updated 4 years ago
• jakorostami / expectation
  Python library for confidence sequences, sequential testing, e-processes, e-values, and game-theoretic probability.
  ☆74Updated last week
• py-why / pywhy-stats
  Python package for (conditional) independence testing and statistical functions related to causality.
  ☆29Updated last month
• canyon289 / causal_inf_bookclub
  Supporting material for the book club
  ☆15Updated 3 years ago
• py-why / pywhy-graphs
  [Experimental] Causal graphs that are networkx-compliant for the py-why ecosystem.
  ☆60Updated 3 weeks ago
• MLResearchAtOSRAM / cause2e
  The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).
  ☆63Updated 6 months ago
• yaronshap / GloballyConsistentRules
  Implementation of algorithms from the paper "Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application…
  ☆25Updated 3 years ago
• RianneSchouten / pyampute
  Missing data amputation and exploration functions for Python
  ☆72Updated 2 years ago
• AlaaLab / conformal-metalearners
  [ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"
  ☆45Updated 2 years ago
• saattrupdan / doubt
  Bringing back uncertainty to machine learning.
  ☆54Updated last year
• koaning / scikit-prune
  Prune your sklearn models
  ☆19Updated last year
• probabl-ai / youtube-appendix
  Resources for some of our education content
  ☆46Updated 2 months ago
• pyartemis / artemis
  A Python package with explanation methods for extraction of feature interactions from predictive models
  ☆32Updated last year
• ptocca / VennABERS
  Fast implementation of Venn-ABERS probabilistic predictors
  ☆75Updated last year
• ericmjl / causality
  In which I play with the ideas surrounding causality
  ☆54Updated 3 years ago
• zalandoresearch / ACIC23-competition
  Data for and description of the ACIC 2023 data competition
  ☆32Updated 2 years ago
• luisroque / bayesian_time_series
  Machine Learning models using a Bayesian approach and often PyMC3
  ☆25Updated 4 years ago
• inovex / justcause
  💊 Comparing causality methods in a fair and just way.
  ☆140Updated 5 years ago
• matheusfacure / exploratory-notebooks
  Unstructured Code with interesting analysis
  ☆37Updated last year
• pymc-devs / pymc-bart
  ☆126Updated last week
• nredell / shapFlex
  An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model
  ☆74Updated 5 years ago