On the public citation graph
Causal Inference on Discrete Data Using Additive Noise Models
0 signed · 154 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/9781119243830.ch12openalex-snapshot
Testing Statistical Hypotheses
inferredcites →https://doi.org/10.1002/series1345openalex-snapshot
Wiley Series in Probability and Statistics
inferredcites →https://doi.org/10.1007/10985687_1openalex-snapshot
A Bayesian Approach to Causal Discovery
inferredcites →https://doi.org/10.1007/978-1-4419-9226-0_5openalex-snapshot
Application of rough sets in the presumptive diagnosis of urinary system diseases
inferredcites →https://doi.org/10.1016/j.neucom.2007.12.023openalex-snapshot
Causal reasoning by evaluating the complexity of conditional densities with kernel methods
inferredcites →https://doi.org/10.1016/s0925-2312(01)00330-7openalex-snapshot
Causality: Models, Reasoning, and Inference
inferredcites →https://doi.org/10.1080/07408170304423openalex-snapshot
Categorical Data Analysis, Second Edition
inferredcites →https://doi.org/10.1142/s1230161210000126openalex-snapshot
Justifying Additive Noise Model-Based Causal Discovery via Algorithmic Information Theory
inferredcites →https://doi.org/10.1145/1553374.1553470openalex-snapshot
Regression by dependence minimization and its application to causal inference in additive noise models
inferredcites →https://doi.org/10.1145/1553374.1553477openalex-snapshot
Detecting the direction of causal time series
inferredcites →https://doi.org/10.1145/3501714.3501732openalex-snapshot
Equivalence and Synthesis of Causal Models
inferredcites →https://doi.org/10.1215/00318108-110-4-639openalex-snapshot
CAUSALITY: MODELS, REASONING AND INFERENCE
inferredcites →https://doi.org/10.2307/3001616openalex-snapshot
Some Methods for Strengthening the Common χ 2 Tests
inferredcites →https://doi.org/10.48550/arxiv.1205.2599openalex-snapshot
On the Identifiability of the Post-Nonlinear Causal Model
inferredcites →https://doi.org/10.48550/arxiv.1205.2640openalex-snapshot
Identifying confounders using additive noise models
inferredcites →https://doi.org/10.7551/mitpress/1754.001.0001openalex-snapshot
Causation, Prediction, and Search
inferredcites →https://doi.org/10.7551/mitpress/2006.003.0007openalex-snapshot
A Bayesian Approach to Causal Discovery
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/9781118947074.ch7openalex-snapshot
Non‐Gaussian Structural Equation Models for Causal Discovery
inferred← citeshttps://doi.org/10.1002/9781119523024.ch2openalex-snapshot
Direction Dependence Analysis
inferred← citeshttps://doi.org/10.1002/cpe.70976openalex-snapshot
Attention‐Guided Causal Structure Learning With Gated Feature Fusion
inferred← citeshttps://doi.org/10.1002/sta4.183openalex-snapshot
Learning directed acyclic graph models based on sparsest permutations
inferred← citeshttps://doi.org/10.1002/wics.1489openalex-snapshot
On nonparametric conditional independence tests for continuous variables
inferred← citeshttps://doi.org/10.1007/978-3-030-10928-8_39openalex-snapshot
Causal Inference on Multivariate and Mixed-Type Data
inferred← citeshttps://doi.org/10.1007/978-3-030-16142-2_36openalex-snapshot
Granger Causality for Heterogeneous Processes
inferred← citeshttps://doi.org/10.1007/978-3-030-21810-2_2openalex-snapshot
Evaluation Methods of Cause-Effect Pairs
inferred← citeshttps://doi.org/10.1007/978-3-030-21810-2_3openalex-snapshot
Learning Bivariate Functional Causal Models
inferred← citeshttps://doi.org/10.1007/978-3-030-21810-2_7openalex-snapshot
Results of the Cause-Effect Pair Challenge
inferred← citeshttps://doi.org/10.1007/978-3-030-47436-2_56openalex-snapshot
ITGH: Information-Theoretic Granger Causal Inference on Heterogeneous Data
inferred← citeshttps://doi.org/10.1007/978-3-030-63833-7_19openalex-snapshot
Causal Inference for Mixed-Type Data in Additive Noise Models
inferred← citeshttps://doi.org/10.1007/978-3-031-78172-8_29openalex-snapshot
Efficient Nonlinear DAG Learning Under Projection Framework
inferred← citeshttps://doi.org/10.1007/978-3-319-12637-1_44openalex-snapshot
A Causal Model for Disease Pathway Discovery
inferred← citeshttps://doi.org/10.1007/978-3-319-21852-6_18openalex-snapshot
Justifying Information-Geometric Causal Inference
inferred← citeshttps://doi.org/10.1007/978-3-319-28379-1_16openalex-snapshot
A Non-Gaussian Approach for Causal Discovery in the Presence of Hidden Common Causes
inferred← citeshttps://doi.org/10.1007/s00500-015-1764-8openalex-snapshot
Multiple-cause discovery combined with structure learning for high-dimensional discrete data and application to stock prediction
inferred← citeshttps://doi.org/10.1007/s00500-016-2281-0openalex-snapshot
An efficient algorithm for large-scale causal discovery
inferred← citeshttps://doi.org/10.1007/s00521-019-04161-5openalex-snapshot
Mining hidden non-redundant causal relationships in online social networks
inferred← citeshttps://doi.org/10.1007/s00521-020-05552-9openalex-snapshot
Understanding the causal structure among the tags in marketing systems
inferred← citeshttps://doi.org/10.1007/s10489-018-1274-3openalex-snapshot
Causal inference and Bayesian network structure learning from nominal data
inferred← citeshttps://doi.org/10.1007/s10489-023-04530-7openalex-snapshot
High-dimensional causal discovery based on heuristic causal partitioning
inferred← citeshttps://doi.org/10.1007/s10618-025-01166-8openalex-snapshot
Detection of unobserved common causes under additive noise models based on NML code for discrete, mixed, and continuous variables
inferred← citeshttps://doi.org/10.1007/s11023-012-9283-1openalex-snapshot
Replacing Causal Faithfulness with Algorithmic Independence of Conditionals
inferred← citeshttps://doi.org/10.1007/s11229-015-0673-9openalex-snapshot
The three faces of faithfulness
inferred← citeshttps://doi.org/10.1007/s12572-021-00302-zopenalex-snapshot
New estimation method for periodic autoregressive time series of order 1 with additive noise
inferred← citeshttps://doi.org/10.1007/s41060-016-0038-6openalex-snapshot
Introduction to the foundations of causal discovery
inferred← citeshttps://doi.org/10.1007/s41237-021-00149-5openalex-snapshot
Causal order identification to address confounding: binary variables
inferred← citeshttps://doi.org/10.1016/j.aei.2025.103139openalex-snapshot
Soft sensing technique for mass customization based on heterogeneous causal graph attention networks
inferred← citeshttps://doi.org/10.1016/j.artint.2012.01.002openalex-snapshot
Information-geometric approach to inferring causal directions
inferred← citeshttps://doi.org/10.1016/j.elerap.2015.06.002openalex-snapshot
Concept drift mining of portfolio selection factors in stock market
inferred← citeshttps://doi.org/10.1016/j.epsr.2026.113323openalex-snapshot
Optimization operation of the integrated traction power supply system based on causal inference
inferred← citeshttps://doi.org/10.1016/j.eswa.2025.127466openalex-snapshot
Causal discovery based on hierarchical reinforcement learning
inferred← citeshttps://doi.org/10.1016/j.eswa.2025.129219openalex-snapshot
VCR-imputer: Discrete data imputation considering variable causal relationships
inferred← citeshttps://doi.org/10.1016/j.heliyon.2023.e17575openalex-snapshot
AI in drug discovery and its clinical relevance
inferred← citeshttps://doi.org/10.1016/j.ijar.2012.09.003openalex-snapshot
Locally averaged Bayesian Dirichlet metrics for learning the structure and the parameters of Bayesian networks
inferred← citeshttps://doi.org/10.1016/j.ins.2021.06.004openalex-snapshot
Combined cause inference: Definition, model and performance
inferred← citeshttps://doi.org/10.1016/j.jbi.2024.104585openalex-snapshot
Counterfactual formulation of patient-specific root causes of disease
inferred← citeshttps://doi.org/10.1016/j.jpdc.2020.12.012openalex-snapshot
Parallel ensemble methods for causal direction inference
inferred← citeshttps://doi.org/10.1016/j.knosys.2025.114145openalex-snapshot
Active differentiable structure learning for clinical causal discovery
inferred← citeshttps://doi.org/10.1016/j.media.2026.104126openalex-snapshot
CLIS: Causality-inspired Longitudinal Image Synthesis and its application to Alzheimer’s disease characterization
inferred← citeshttps://doi.org/10.1016/j.neucom.2020.01.021openalex-snapshot
Effective and scalable causal partitioning based on low-order conditional independent tests
inferred← citeshttps://doi.org/10.1016/j.neunet.2018.03.013openalex-snapshot
A multivariate additive noise model for complete causal discovery
inferred← citeshttps://doi.org/10.1016/j.neunet.2020.01.006openalex-snapshot
FOM: Fourth-order moment based causal direction identification on the heteroscedastic data
inferred← citeshttps://doi.org/10.1016/j.neunet.2026.109426openalex-snapshot
Causal discovery from time-series discrete data in the presence of latent confounders
inferred← citeshttps://doi.org/10.1016/j.patcog.2023.110149openalex-snapshot
Coresets for fast causal discovery with the additive noise model
inferred← citeshttps://doi.org/10.1016/j.procs.2023.08.062openalex-snapshot
A study of factors influencing financial stock prices based on causal inference
inferred← citeshttps://doi.org/10.1016/j.schres.2024.07.005openalex-snapshot
Unraveling schizophrenia's genetic complexity through advanced causal inference and chromatin 3D conformation
inferred← citeshttps://doi.org/10.1017/s0140525x23002273openalex-snapshot
Beyond integrative experiment design: Systematic experimentation guided by causal discovery AI
inferred← citeshttps://doi.org/10.1038/s41598-020-60682-3openalex-snapshot
Shared Causal Paths underlying Alzheimer’s dementia and Type 2 Diabetes
inferred← citeshttps://doi.org/10.1089/cmb.2021.0676openalex-snapshot
Genome-Wide Causation Studies of Complex Diseases
inferred← citeshttps://doi.org/10.1109/3pgcic.2014.133openalex-snapshot
Discovering Many-to-One Causality in Software Project Risk Analysis
inferred← citeshttps://doi.org/10.1109/access.2017.2746539openalex-snapshot
Inferring Causal Direction From Multi-Dimensional Causal Networks for Assessing Harmful Factors in Security Analysis
inferred← citeshttps://doi.org/10.1109/access.2020.2965093openalex-snapshot
Distinguish Markov Equivalence Classes from Large-Scale Linear Non-Gaussian Data
inferred← citeshttps://doi.org/10.1109/acpee60788.2024.10532571openalex-snapshot
Extraction of Influencing Variables for Power System Static Stability Indicators Based on Reciprocal Information Entropy Causal Inference
inferred← citeshttps://doi.org/10.1109/bigdata55660.2022.10020351openalex-snapshot
Detection of Unobserved Common Cause in Discrete Data Based on the MDL Principle
inferred← citeshttps://doi.org/10.1109/cisai54367.2021.00137openalex-snapshot
Machine Learning Regressed Causal Inference for Discrete ANM
inferred← citeshttps://doi.org/10.1109/compsac48688.2020.0-231openalex-snapshot
An Information Theoretic Learning for Causal Direction Identification
inferred← citeshttps://doi.org/10.1109/cse-euc.2017.59openalex-snapshot
Fast Causal Division for Supporting High Dimensional Causal Discovery
inferred← citeshttps://doi.org/10.1109/cse-euc.2017.76openalex-snapshot
An Approach for Inferring Causal Directions from Multi-Dimensional Networks
inferred← citeshttps://doi.org/10.1109/csei50228.2020.9142500openalex-snapshot
Research on the Application of a High-dimensional Bayesian Network in the Evaluation of Ethnic-Chinese Bilingual Teaching
inferred← citeshttps://doi.org/10.1109/icdar.2013.267openalex-snapshot
Bayesian Network Structure Learning and Inference Methods for Handwriting
inferred← citeshttps://doi.org/10.1109/icdm51629.2021.00082openalex-snapshot
Nonlinear Causal Structure Learning for Mixed Data
inferred← citeshttps://doi.org/10.1109/isit.2017.8006772openalex-snapshot
Entropic Causality and Greedy Minimum Entropy Coupling
inferred← citeshttps://doi.org/10.1109/jas.2019.1911603openalex-snapshot
An overview and perspectives on bidirectional intelligence: Lmser duality, double IA harmony, and causal computation
inferred← citeshttps://doi.org/10.1109/jiot.2025.3647868openalex-snapshot
ANHP: Adaptive Neural Hawkes Processes for Causal Structure Learning on Event Sequences
inferred← citeshttps://doi.org/10.1109/ssp49050.2021.9513735openalex-snapshot
A Subsampling-Based Method for Causal Discovery on Discrete Data
inferred← citeshttps://doi.org/10.1109/tcbb.2022.3149864openalex-snapshot
Causal Gene Identification Using Non-Linear Regression-Based Independence Tests
inferred← citeshttps://doi.org/10.1109/tcyb.2020.3010004openalex-snapshot
Learning Causal Structures Based on Divide and Conquer
inferred← citeshttps://doi.org/10.1109/tit.2019.2927530openalex-snapshot
Innovation Representation of Stochastic Processes With Application to Causal Inference
inferred← citeshttps://doi.org/10.1109/tnnls.2016.2556724openalex-snapshot
Understanding Social Causalities Behind Human Action Sequences
inferred← citeshttps://doi.org/10.1109/tnnls.2020.3045812openalex-snapshot
Causal Discovery in Linear Non-Gaussian Acyclic Model With Multiple Latent Confounders
inferred← citeshttps://doi.org/10.1109/tnnls.2022.3213641openalex-snapshot
Causal Discovery on Discrete Data via Weighted Normalized Wasserstein Distance
inferred← citeshttps://doi.org/10.1109/tpami.2025.3553957openalex-snapshot
Addressing Information Asymmetry: Deep Temporal Causality Discovery for Mixed Time Series
inferred← citeshttps://doi.org/10.1109/tpami.2026.3689960openalex-snapshot
Autonomous Causal Discovery: Evaluating LLMs’ Priors and Constraint Strategies for Reliability
inferred← citeshttps://doi.org/10.1109/tpami.2026.3721159openalex-snapshot
Kolmogorov-Arnold Causal Generative Models
inferred← citeshttps://doi.org/10.1111/rssb.12235openalex-snapshot
Kernel-Based Tests for Joint Independence
inferred← citeshttps://doi.org/10.1137/1.9781611974010.102openalex-snapshot
Causal Inference by Direction of Information
inferred← citeshttps://doi.org/10.1145/2700477openalex-snapshot
Causal Discovery on Discrete Data with Extensions to Mixture Model
inferred← citeshttps://doi.org/10.1145/3325708openalex-snapshot
Measuring Conditional Independence by Independent Residuals for Causal Discovery
inferred← citeshttps://doi.org/10.1145/3589301openalex-snapshot
XInsight: eXplainable Data Analysis Through The Lens of Causality
inferred← citeshttps://doi.org/10.1162/neco_a_00820openalex-snapshot
Causal Inference on Discrete Data via Estimating Distance Correlations
inferred← citeshttps://doi.org/10.1186/s12911-018-0597-7openalex-snapshot
Causal risk factor discovery for severe acute kidney injury using electronic health records
inferred← citeshttps://doi.org/10.1364/qim.2021.f2c.3openalex-snapshot
Quantum Entropic Causal Inference
inferred← citeshttps://doi.org/10.1371/journal.pone.0204755openalex-snapshot
Inferring causal pathways among three or more variables from steady-state correlations in a homeostatic system
inferred← citeshttps://doi.org/10.1515/jci-2016-0013openalex-snapshot
Causal Inference via Algebraic Geometry: Feasibility Tests for Functional Causal Structures with Two Binary Observed Variables
inferred← citeshttps://doi.org/10.15446/cuad.econ.v37n75.69832openalex-snapshot
Tools for causal inference from cross-sectional innovation surveys with continuous or discrete variables: Theory and applications
inferred← citeshttps://doi.org/10.1609/aaai.v31i1.10698openalex-snapshot
Causal Discovery Using Regression-Based Conditional Independence Tests
inferred← citeshttps://doi.org/10.1609/aaai.v32i1.11555openalex-snapshot
Measuring Conditional Independence by Independent Residuals: Theoretical Results and Application in Causal Discovery
inferred← citeshttps://doi.org/10.1609/aaai.v33i01.33013108openalex-snapshot
Recursively Learning Causal Structures Using Regression-Based Conditional Independence Test
inferred← citeshttps://doi.org/10.1609/aaai.v36i7.20707openalex-snapshot
A Hybrid Causal Structure Learning Algorithm for Mixed-Type Data
inferred← citeshttps://doi.org/10.1609/aaai.v38i15.29586openalex-snapshot
Effective Causal Discovery under Identifiable Heteroscedastic Noise Model
inferred← citeshttps://doi.org/10.1609/aaai.v39i25.34888openalex-snapshot
Counterfactual Identification Under Monotonicity Constraints
inferred← citeshttps://doi.org/10.17562/pb-52-7openalex-snapshot
Cipher Image Damage: An Application of Filters
inferred← citeshttps://doi.org/10.17615/amaf-6630openalex-snapshot
Bayesian Estimation of Causal Direction in Acyclic Structural Equation Models with Individual-specific Confounder Variables and Non-Gaussian Distributions
inferred← citeshttps://doi.org/10.17863/cam.125386openalex-snapshot
Structure Learning for Directed Trees
inferred← citeshttps://doi.org/10.2333/bhmk.41.65openalex-snapshot
Lingam: Non-Gaussian Methods for Estimating Causal Structures
inferred← citeshttps://doi.org/10.24963/ijcai.2018/711openalex-snapshot
Mixed Causal Structure Discovery with Application to Prescriptive Pricing
inferred← citeshttps://doi.org/10.3150/22-bej1529openalex-snapshot
On Azadkia–Chatterjee’s conditional dependence coefficient
inferred← citeshttps://doi.org/10.3389/fgene.2018.00238openalex-snapshot
Application of Causal Inference to Genomic Analysis: Advances in Methodology
inferred← citeshttps://doi.org/10.3389/fgene.2021.651812openalex-snapshot
MRPC: An R Package for Inference of Causal Graphs
inferred← citeshttps://doi.org/10.3389/frobt.2016.00071openalex-snapshot
An Information Criterion for Inferring Coupling of Distributed Dynamical Systems
inferred← citeshttps://doi.org/10.3390/math12091375openalex-snapshot
Hidden Variable Discovery Based on Regression and Entropy
inferred← citeshttps://doi.org/10.3390/molecules23071729openalex-snapshot
Causal Discovery Combining K2 with Brain Storm Optimization Algorithm
inferred← citeshttps://doi.org/10.3758/s13428-018-1031-xopenalex-snapshot
Direction dependence analysis: A framework to test the direction of effects in linear models with an implementation in SPSS
inferred← citeshttps://doi.org/10.3929/ethz-a-007597940openalex-snapshot
Restricted structural equation models for causal inference
inferred← citeshttps://doi.org/10.48550/arxiv.1112.2738openalex-snapshot
Robust Learning via Cause-Effect Models
inferred← citeshttps://doi.org/10.48550/arxiv.1307.0366openalex-snapshot
Learning directed acyclic graphs based on sparsest permutations
inferred← citeshttps://doi.org/10.48550/arxiv.1309.6779openalex-snapshot
Causal Discovery with Continuous Additive Noise Models
inferred← citeshttps://doi.org/10.48550/arxiv.1309.6843openalex-snapshot
A Sound and Complete Algorithm for Learning Causal Models from Relational Data
inferred← citeshttps://doi.org/10.48550/arxiv.1310.6778openalex-snapshot
Bayesian estimation of possible causal direction in the presence of latent confounders using a linear non-Gaussian acyclic structural equation model with individual-specific effects
inferred← citeshttps://doi.org/10.48550/arxiv.1312.5770openalex-snapshot
Consistency of Causal Inference under the Additive Noise Model
inferred← citeshttps://doi.org/10.48550/arxiv.1401.5636openalex-snapshot
Causal Discovery in a Binary Exclusive-or Skew Acyclic Model: BExSAM
inferred← citeshttps://doi.org/10.48550/arxiv.1412.3773openalex-snapshot
Distinguishing cause from effect using observational data: methods and benchmarks
inferred← citeshttps://doi.org/10.48550/arxiv.1605.04056openalex-snapshot
Causal Discovery for Manufacturing Domains
inferred← citeshttps://doi.org/10.48550/arxiv.1611.01504openalex-snapshot
Estimating Causal Direction and Confounding of Two Discrete Variables
inferred← citeshttps://doi.org/10.48550/arxiv.1701.08254openalex-snapshot
Entropic Causality and Greedy Minimum Entropy Coupling
inferred← citeshttps://doi.org/10.48550/arxiv.1702.06385openalex-snapshot
Causal Inference on Multivariate and Mixed Type Data
inferred← citeshttps://doi.org/10.48550/arxiv.1707.01283openalex-snapshot
SADA: A General Framework to Support Robust Causation Discovery with Theoretical Guarantee
inferred← citeshttps://doi.org/10.48550/arxiv.1802.05889openalex-snapshot
Combining Linear Non-Gaussian Acyclic Model with Logistic Regression Model for Estimating Causal Structure from Mixed Continuous and Discrete Data
inferred← citeshttps://doi.org/10.48550/arxiv.1804.03206openalex-snapshot
Merging joint distributions via causal model classes with low VC dimension
inferred← citeshttps://doi.org/10.48550/arxiv.1906.02226openalex-snapshot
Gradient-Based Neural DAG Learning
inferred← citeshttps://doi.org/10.48550/arxiv.2007.15047openalex-snapshot
Information-Theoretic Approximation to Causal Models
inferred← citeshttps://doi.org/10.48550/arxiv.2010.03095openalex-snapshot
Gradient-based Causal Structure Learning with Normalizing Flow
inferred← citeshttps://doi.org/10.48550/arxiv.2110.01430openalex-snapshot
Causality and Generalizability: Identifiability and Learning Methods
inferred← citeshttps://doi.org/10.5555/2627435.2670315openalex-snapshot
Causal discovery with continuous additive noise models
inferred← citeshttps://doi.org/10.7150/jca.52183openalex-snapshot
Machine learning classifiers for predicting 3-year progression-free survival and overall survival in patients with gliomas after surgery
inferred← citeshttps://doi.org/10.7275/6041512.0openalex-snapshot
Causal Discovery for Relational Domains: Representation, Reasoning, and Learning
inferred← citeshttps://doi.org/10.7717/peerj-cs.169openalex-snapshot
Analysis of cause-effect inference by comparing regression errors
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.