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Causality and causal inference for engineers: Beyond correlation, regression, prediction and artificial intelligence
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/wics.1581openalex-snapshot
Data integration in causal inference
inferredcites →https://doi.org/10.1002/widm.1449openalex-snapshot
Methods and tools for causal discovery and causal inference
inferredcites →https://doi.org/10.1007/978-3-476-05728-0_9644-1openalex-snapshot
Hume, David: A Treatise of Human Nature
inferredcites →https://doi.org/10.1007/978-94-009-4622-4_34openalex-snapshot
Causality and Explanation
inferredcites →https://doi.org/10.1038/nmeth.4642openalex-snapshot
Statistics versus machine learning
inferredcites →https://doi.org/10.1038/s42256-019-0048-xopenalex-snapshot
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
inferredcites →https://doi.org/10.1080/01621459.2020.1801279openalex-snapshot
Handbook of Graphical Models
inferredcites →https://doi.org/10.1090/notiopenalex-snapshot
Notices of the American Mathematical Society
inferredcites →https://doi.org/10.1111/insr.12011_5openalex-snapshot
Probability for Statistics and Machine Learning: Fundamentals and Advanced Topics by Anirban DasGupta
inferredcites →https://doi.org/10.1146/annurev-statistics-031017-100630openalex-snapshot
Causal Structure Learning
inferredcites →https://doi.org/10.1198/016214504000001880openalex-snapshot
Causal Inference Using Potential Outcomes
inferredcites →https://doi.org/10.1198/tech.2003.s770openalex-snapshot
The Elements of Statistical Learning
inferredcites →https://doi.org/10.1214/09-ss057openalex-snapshot
Causal inference in statistics: An overview
inferredcites →https://doi.org/10.2307/1912791openalex-snapshot
Investigating Causal Relations by Econometric Models and Cross-spectral Methods
inferredcites →https://doi.org/10.2307/2179802openalex-snapshot
Causality from the Point of View of the Engineer
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Teaching Variables Interaction Effects Through a Battery‐Aging Case Study in Undergraduate Engineering
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A Survey on Causal Inference‐Driven Data Bias Optimization in Recommendation Systems: Principles, Opportunities and Challenges
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High-resolution snow depth modeling in South Korea using radar-based precipitation data
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On the Philosophical Naivety of Engineers in the Age of Machine Learning
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Dataism, skepticism, and intuition for interpretable machine learning
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When to use machine learning? And which problems stand to benefit?
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KnowEntityRec: entity-centric knowledge perception graph neural network for news recommendation
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HPNewsRec: Hybrid perception entity-centric personalized news recommendation
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Information science for materials science
inferred← citeshttps://doi.org/10.1016/j.cie.2025.111704openalex-snapshot
Fundamental flaws of physics-informed neural networks and explainability methods in engineering systems
inferred← citeshttps://doi.org/10.1016/j.dte.2025.100057openalex-snapshot
Intuitive tests to validate machine learning models against physics and domain knowledge
inferred← citeshttps://doi.org/10.1016/j.ece.2025.06.006openalex-snapshot
Causation in chemical engineering education: Application of machine learning in fault diagnosis
inferred← citeshttps://doi.org/10.1016/j.materresbull.2026.114251openalex-snapshot
Materials by machines: A review on intuition and knowledge-driven learning for rapid discovery and optimization
inferred← citeshttps://doi.org/10.1016/j.optlastec.2026.115167openalex-snapshot
Causal-YOLO: enhancing object detection in remote sensing imagery through causal feature alignment
inferred← citeshttps://doi.org/10.1038/s41598-026-42723-5openalex-snapshot
KG-EIGNN: a knowledge graph based graph neural network for fault detection in industrial systems
inferred← citeshttps://doi.org/10.1061/jsendh.steng-15222openalex-snapshot
Making the Black Box Transparent: State of the Art in Explainable Machine Learning for Structural Design and Assessment
inferred← citeshttps://doi.org/10.1080/13658816.2026.2680024openalex-snapshot
DML-Geo: an ensemble double machine learning framework for estimating spatially heterogeneous causal effects
inferred← citeshttps://doi.org/10.1093/pnasnexus/pgae461openalex-snapshot
Artificial intelligence in food and nutrition evidence: The challenges and opportunities
inferred← citeshttps://doi.org/10.1109/bigdata66926.2025.11401645openalex-snapshot
DODO: Causal Structure Learning with Budgeted Interventions
inferred← citeshttps://doi.org/10.1109/prmvai65741.2025.11108465openalex-snapshot
Prescriptive Analytics for Next-Gen Supply Chains: Integrating Causal AI with Digital Twin Technologies
inferred← citeshttps://doi.org/10.1109/sami68106.2026.11420585openalex-snapshot
Conformal Counterfactual Forecasting with Reduced Uncertainty for Time Series Predictions
inferred← citeshttps://doi.org/10.1177/03611981241306754openalex-snapshot
Causal Graph Discovery for Urban Bus Operation Delays: A Case Study in Stockholm
inferred← citeshttps://doi.org/10.1186/s40537-025-01346-9openalex-snapshot
A review of machine learning with small and limited data
inferred← citeshttps://doi.org/10.2139/ssrn.7240416openalex-snapshot
Data Driven Machine Learning in Evacuation Dynamics: Trends, Insights and Opportunities
inferred← citeshttps://doi.org/10.2188/jea.je20240412openalex-snapshot
What Epidemiologists Can Do in the Era of Machine Learning and Artificial Intelligence
inferred← citeshttps://doi.org/10.3390/buildings16030669openalex-snapshot
Prior-Knowledge-Guided Missing Data Imputation for Bridge Cracks: A Temperature-Driven SP-VMD-CNN-GRU Framework
inferred← citeshttps://doi.org/10.3390/informatics13080136openalex-snapshot
How Data Quality Impacts Decision Outcomes: Scoping Review, Methodological Development, and Empirical Demonstration
inferred← citeshttps://doi.org/10.68159/o220486108openalex-snapshot
Conceptual Treatments of Causality in Materials Informatics — From Correlation to Intervention: A Review Study
inferred← citeshttps://doi.org/10.68159/w708736063openalex-snapshot
Causality in Materials Informatics — Conceptual Progress, Limitations, and Future Directions
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