Alternatives and similar repositories for sparse_shift

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

• azizilab / sdcd
  Stable Differentiable Causal Discovery (SDCD)
  ☆22Updated 10 months ago
• uhlerlab / causaldag
  Python package for the creation, manipulation, and learning of Causal DAGs
  ☆151Updated 2 years ago
• uhlerlab / conditional_independence
  Parametric and non-parametric conditional independence testing.
  ☆10Updated 4 years ago
• Genentech / dcdfg
  ☆24Updated 2 years ago
• larslorch / stadion
  Causal Modeling with Stationary Diffusions, AISTATS 2024
  ☆18Updated 2 months ago
• clarafy / conformal-for-design
  ☆30Updated 2 years ago
• slachapelle / dcdi
  Repository for "Differentiable Causal Discovery from Interventional Data"
  ☆74Updated 3 years ago
• BorgwardtLab / filtration_curves
  Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'
  ☆18Updated last year
• rpatrik96 / nl-causal-representations
  This is the code for the paper Jacobian-based Causal Discovery with Nonlinear ICA, demonstrating how identifiable representations (partic…
  ☆18Updated 8 months ago
• lazaratan / dyn-gfn
  DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks
  ☆53Updated last year
• causalbench / causalbench
  ☆41Updated 6 months ago
• sweichwald / tidybench
  TIme series DiscoverY BENCHmark (tidybench)
  ☆37Updated last year
• Genentech / nodags-flows
  ☆9Updated last year
• larslorch / avici
  Amortized Inference for Causal Structure Learning, NeurIPS 2022
  ☆62Updated 3 months ago
• Ashkan-Soleymani98 / CORTH-Features-Causal-Feature-Selection-via-Orthogonal-Search
  ☆12Updated 2 years ago
• ermongroup / BCD-Nets
  Code for `BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery`, Neurips 2021
  ☆26Updated 3 years ago
• navid-naderi / WEGL
  The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
  ☆35Updated 4 years ago
• seedatnabeel / TE-CDE
  Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)
  ☆27Updated 2 years ago
• bradyneal / realcause
  Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…
  ☆74Updated 4 years ago
• juangamella / causal-chamber
  Public dataset repository for the Causal Chamber Project
  ☆35Updated 2 weeks ago
• phlippe / ENCO
  Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"
  ☆82Updated last year
• msesia / arc
  Adaptive and Reliable Classification: efficient conformity scores for multi-class classification problems
  ☆31Updated 2 years ago
• ArnoVel / structure-identification
  Uses several statistical tests / algorithms on marginal / conditional distributions
  ☆8Updated last year
• akekic / causal-component-analysis
  ☆25Updated last year
• piomonti / carefl
  Code for "Causal autoregressive flows" - AISTATS, 2021
  ☆45Updated 4 years ago
• yuachen / CausalDA
  Code to reproduce the numerical experiments in the paper Domain adaptation under structural causal models by Yuansi Chen and Peter Bühlma…
  ☆18Updated 3 years ago
• anndvision / quince
  Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding
  ☆22Updated 2 years ago
• diviyank / SAM
  Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)
  ☆52Updated 4 years ago
• felixleopoldo / benchpress
  Scalable open-source software to run, develop, and benchmark causal discovery algorithms
  ☆69Updated 2 weeks ago
• zecevic-matej / Not-All-Causal-Inference-is-the-Same
  Official code repository to the corresponding paper.
  ☆29Updated last year