mlsanityData to 7 Oct 2026

Causal Mosaic: Cause-Effect Inference via Nonlinear ICA and Ensemble Method

arXiv 2001.01894 ↗First posted 7 Jan 2020stat.ML cs.LGcited by 16

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Abstract (arXiv)

We address the problem of distinguishing cause from effect in bivariate setting. Based on recent developments in nonlinear independent component analysis (ICA), we train nonparametrically general nonlinear causal models that allow non-additive noise. Further, we build an ensemble framework, namely Causal Mosaic, which models a causal pair by a mixture of nonlinear models. We compare this method with other recent methods on artificial and real world benchmark datasets, and our method shows state-of-the-art performance.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Jan 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 7; 2022: 2; 2023: 4; 2024: 2; 2025: 0; 2026: 1.

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  1. 2023Causal Reasoning and Large Language Models: Opening a New Frontier for Causalitycited by 348
  2. 2021D'ya like DAGs? A Survey on Structure Learning and Causal Discoverycited by 209
  3. 2021Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICAcited by 64
  4. 2022LMPriors: Pre-Trained Language Models as Task-Specific Priorscited by 56
  5. 2023Causal Representation Learning Made Identifiable by Grouping of Observational Variablescited by 30
  6. 2021Intact-VAE: Estimating Treatment Effects under Unobserved Confoundingcited by 10
  7. 2023Emerging Synergies in Causality and Deep Generative Models: A Surveycited by 10
  8. 2021β-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlapcited by 8
  9. 2021Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal Effectscited by 7
  10. 2021Representation learning for maximization of MI, nonlinear ICA and nonlinear subspaces with robust density ratio estimationcited by 4
  11. 2021Towards Principled Causal Effect Estimation by Deep Identifiable Modelscited by 4
  12. 2022A Free Lunch with Influence Functions? Improving Neural Network Estimates with Concepts from Semiparametric Statisticscited by 4
4 more
  1. 2023Identifiable Feature Learning for Spatial Data with Nonlinear ICAcited by 4
  2. 2024Identifying General Mechanism Shifts in Linear Causal Representationscited by 4
  3. 2026Topological Residual Asymmetry for Bivariate Causal Directioncited by 2
  4. 2024Identifiability of a statistical model with two latent vectors: Importance of the dimensionality relation and application to graph embeddingcited by 0