Alternatives and similar repositories for KDD24-Conformal

Users that are interested in KDD24-Conformal are comparing it to the libraries listed below

• AlaaLab / conformal-metalearners
  [ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"
  ☆44Updated last year
• chritoth / active-bayesian-causal-inference
  Active Bayesian Causal Inference (Neurips'22)
  ☆58Updated last year
• msesia / conditional-conformal-pvalues
  Conditional calibration of conformal p-values for outlier detection.
  ☆36Updated 2 years ago
• CausalAIBook / MetricsMLNotebooks
  Notebooks for Applied Causal Inference Powered by ML and AI
  ☆129Updated 5 months ago
• zalandoresearch / ACIC23-competition
  Data for and description of the ACIC 2023 data competition
  ☆32Updated 2 years ago
• ThatShelbs / CausalInferenceTimeSeries
  Causal Inference for Time Series Data (with CausalML Demo)
  ☆14Updated 2 years ago
• deshen24 / syntheticNN
  ☆24Updated 3 years ago
• FMenchetti / CausalArima
  An R package to estimate the effect of interventions on univariate time series using ARIMA models
  ☆23Updated last year
• amazon-science / azcausal
  Causal Inference in Python
  ☆44Updated 7 months ago
• AlxndrMlk / causality
  Notes, exercises and other materials related to causal inference, causal discovery and causal ML.
  ☆143Updated last month
• isgibbs / DtACI
  ☆17Updated 4 months ago
• max-little / GRAPL
  GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference
  ☆83Updated 8 months ago
• py-why / pywhy-stats
  Python package for (conditional) independence testing and statistical functions related to causality.
  ☆28Updated 2 months ago
• lorismichel / drf
  Distributional Random Forests (Cevid et al., 2020)
  ☆44Updated 2 years ago
• vdorie / npci
  Non-parametrics for Causal Inference
  ☆49Updated 3 years ago
• anishazaveri / austen_plots
  Demo data and code for "Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding".
  ☆26Updated 3 years ago
• ostojanovic / causalML
  ☆33Updated 11 months ago
• callmespring / CausalRL
  Implementation of "Dynamic Causal Effects Evaluation in A/B Testing with a Reinforcement Learning Framework" (JASA 2023)
  ☆32Updated last year
• causalens / cai-causal-graph
  A Causal AI package for causal graphs.
  ☆60Updated 4 months ago
• dandls / moc
  Multi-Objective Counterfactuals
  ☆42Updated 3 years ago
• bernardodionisi / differences
  difference-in-differences in Python
  ☆104Updated last year
• bradyneal / realcause
  Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…
  ☆77Updated 4 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
• yuachen / CausalDA
  Code to reproduce the numerical experiments in the paper Domain adaptation under structural causal models by Yuansi Chen and Peter Bühlma…
  ☆18Updated 4 years ago
• socket778 / XBCF
  R and python implementations of Accelerated Bayesian Causal Forest.
  ☆25Updated last year
• d2cml-ai / mgtecon634_py
  This tutorial will introduce key concepts in machine learning-based causal inference. This tutorial is used by professor Susan Athey in t…
  ☆12Updated 2 years ago
• valeman / Multi-class-probabilistic-classification
  Multi-class probabilistic classification using inductive and cross Venn–Abers predictors
  ☆49Updated 3 years ago
• yaronshap / GloballyConsistentRules
  Implementation of algorithms from the paper "Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application…
  ☆25Updated 3 years ago
• bradyneal / causal-book-code
  ☆78Updated 5 years ago
• xqnwang / conformalForecast
  Methods and tools for multistep-ahead time series conformal prediction.
  ☆38Updated 5 months ago