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Why does a phenomenon occur? Addressing this question is central to most scientific inquiries and often relies on simulations of scientific models.
Status and Improvements of Coupled General Circulation Models
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Causation, prediction, and search. 2nd edn in, 2001
P Sprites, C Glymour, and R Scheines · 2001
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On implicit and explicit discretization schemes for parabolic spdes in any dimension
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From Ordinary Differential Equations to Structural Causal Models: the deterministic case
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Great expectations: using whole-brain computational connectomics for understanding neuropsychiatric disorders
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Dynamic models of large-scale brain activity
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Causal Consistency of Structural Equation Models
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Approximate Causal Abstractions
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Causal structure-based root cause analysis of outliers
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Causal Abstraction for Faithful Model Interpretation
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Uncovering the organization of neural circuits with generalized phase locking analysis
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Linear Causal Disentanglement via Interventions
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Counterfactuals uncover the modular structure of deep generative models
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Foundations of structural causal models with cycles and latent variables
Stephan Bongers, Patrick Forré, Jonas Peters, and Joris M Mooij · 2021
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Causal Abstractions of Neural Networks
Atticus Geiger, Hanson Lu, Thomas Icard, and Christopher Potts · 2021
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Compositional Abstraction Error and a Category of Causal Models
Eigil F Rischel and Sebastian Weichwald · 2021
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Institutiones calculi integralis , volume 4
Leonhard Euler
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Nonparametric Identifiability of Causal Representations from Unknown Interventions
Julius von Kügelgen, Michel Besserve, Liang Wendong, Luigi Gresele, Armin Kekić, Elias Bareinboim, David M Blei, and Bernhard Schölkopf
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Causal component analysis
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Jointly Learning Consistent Causal Abstractions Over Multiple Interventional Distributions
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Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations
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Meaningful Causal Aggregation and Paradoxical Confounding
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