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Causal Discovery

24 papers with code · Knowledge Base

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Latest papers with code

Autoregressive flow-based causal discovery and inference

18 Jul 2020piomonti/AffineFlowCausalInf

We posit that autoregressive flow models are well-suited to performing a range of causal inference tasks - ranging from causal discovery to making interventional and counterfactual predictions.

CAUSAL DISCOVERY CAUSAL INFERENCE

3
18 Jul 2020

Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data

18 Jun 2020loeweX/AmortizedCausalDiscovery

Standard causal discovery methods must fit a new model whenever they encounter samples from a new underlying causal graph.

CAUSAL DISCOVERY TIME SERIES

36
18 Jun 2020

Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets

7 Mar 2020jakobrunge/tigramite

We consider causal discovery from time series using conditional independence (CI) based network learning algorithms such as the PC algorithm.

CAUSAL DISCOVERY TIME SERIES

311
07 Mar 2020

Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering

NeurIPS 2019 Biwei-Huang/Specific-and-Shared-Causal-Relation-Modeling-and-Mechanism-Based-Clustering

The learned SSCM gives the specific causal knowledge for each individual as well as the general trend over the population.

CAUSAL DISCOVERY

0
01 Dec 2019

Learning Sparse Nonparametric DAGs

29 Sep 2019xunzheng/notears

We develop a framework for learning sparse nonparametric directed acyclic graphs (DAGs) from data.

CAUSAL DISCOVERY

163
29 Sep 2019

Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation

NeurIPS 2019 TURuibo/Neuropathic-Pain-Diagnosis-Simulator

We show that the data generated from our simulator have similar statistics as real-world data.

CAUSAL DISCOVERY

4
04 Jun 2019

Causal Discovery with Cascade Nonlinear Additive Noise Models

23 May 2019DMIRLAB-Group/CANM

In this work, we propose a cascade nonlinear additive noise model to represent such causal influences--each direct causal relation follows the nonlinear additive noise model but we observe only the initial cause and final effect.

CAUSAL DISCOVERY

5
23 May 2019

Causal Discovery Toolbox: Uncover causal relationships in Python

6 Mar 2019FenTechSolutions/CausalDiscoveryToolbox

This paper presents a new open source Python framework for causal discovery from observational data and domain background knowledge, aimed at causal graph and causal mechanism modeling.

CAUSAL DISCOVERY

335
06 Mar 2019

Testing Conditional Independence in Supervised Learning Algorithms

28 Jan 2019dswatson/cpi

We propose the conditional predictive impact (CPI), a consistent and unbiased estimator of the association between one or several features and a given outcome, conditional on a reduced feature set.

CAUSAL DISCOVERY MODEL SELECTION

4
28 Jan 2019