Causal Identification

Benchmarks archive 2025-07-28

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Libraries

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Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

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Most implemented papers archive 2025-07-28

14 shown of 14 papers with code (48 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Adapting Text Embeddings for Causal Inference
  29 May 2019 4 repositories listed
  To address this challenge, we develop causally sufficient embeddings, low-dimensional document representations that preserve sufficient information for causal identification and allow for efficient estimation of causal…
• BISCUIT: Causal Representation Learning from Binary Interactions
  16 Jun 2023 2 repositories listed
  Identifying the causal variables of an environment and how to intervene on them is of core value in applications such as robotics and embodied AI.
• The Causal-Neural Connection: Expressiveness, Learnability, and Inference
  2 Jul 2021 2 repositories listed Syntology ran 1 of 2 samples · 1 unverified
  Given this property, one may be tempted to surmise that a collection of neural nets is capable of learning any SCM by training on data generated by that SCM.
• Identifying while Learning for Document Event Causality Identification
  31 May 2024 1 repository listed
  Event Causality Identification (ECI) aims to detect whether there exists a causal relation between two events in a document.
• Hierarchical Causal Models
  10 Jan 2024 1 repository listed
  Scientists often want to learn about cause and effect from hierarchical data, collected from subunits nested inside units.
• Neural Network Parameter-optimization of Gaussian pmDAGs
  25 Sep 2023 1 repository listed
  We present the first duality between parameter optimization of a latent variable model and training a feed-forward neural network in the parameter space of the assumed family of distributions.
• RCT Rejection Sampling for Causal Estimation Evaluation
  27 Jul 2023 1 repository listed Syntology ran 3 of 3 samples · 0 unverified
  We contribute a new sampling algorithm, which we call RCT rejection sampling, and provide theoretical guarantees that causal identification holds in the observational data to allow for valid comparisons to the…
• Causal Discovery via Conditional Independence Testing with Proxy Variables
  9 May 2023 1 repository listed Syntology ran 1 of 3 samples · 2 unverified · 3 pointer-only (licence)
  Distinguishing causal connections from correlations is important in many scenarios.
• Causal Discovery from Subsampled Time Series with Proxy Variables
  9 May 2023 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  Based on these, we can leverage the proxies to remove the bias induced by the hidden variables and hence achieve identifiability.
• pgmpy: A Python Toolkit for Bayesian Networks
  17 Apr 2023 1 repository listed
  Bayesian Networks (BNs) are used in various fields for modeling, prediction, and decision making.
• Flow-based Perturbation for Cause-effect Inference
  17 Oct 2022 1 repository listed
  A new causal discovery method is introduced to solve the bivariate causal discovery problem.
• The Effect of Noise Level on Causal Identification with Additive Noise Models
  24 Aug 2021 1 repository listed
  Unfortunately, one aspect of these methods has not received much attention until now: what is the impact of different noise levels on the ability of these methods to identify the direction of the causal relationship.
• Invariant Representation Learning for Treatment Effect Estimation
  24 Nov 2020 1 repository listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)
  To address this challenge, practitioners collect and adjust for the covariates, hoping that they adequately correct for confounding.
• Identifying Causal Structure in Dynamical Systems
  6 Jun 2020 1 repository listed
  In this paper, we propose a method that identifies the causal structure of control systems.

Syntology lines on 5 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.