Causal Discovery

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17 papers in the last four weeks, up 183% on the four weeks before. 0.2% of all new papers.

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  1. Adversarial Causal Intervention Falsification

    Aug 5, 2026Mojtaba EslamiStructural Causal ModelsCausal Discovery

    University of Calgary

  2. SVI-DAG: A Structured Variational Inference Approach to Bayesian Causal Discovery

    Aug 5, 2026Shrenik ZinageCausal DiscoveryVariational Inference

    Massachusetts Institute of Technology · This work was conducted while the author was a PhD student at Purdue University, independently of the author’s dissertation research.

  3. GENESIS: Towards Explainable Causal Discovery

    Aug 4, 2026Abhinav Thorat, Ravi Kumar Kolla, Vishak K Bhat +2Causal DiscoveryCausal Structure Learning

    User Engagement Research, Sony Research India

  4. GoT-CD: Graph-of-Thoughts Causal Discovery and the Fragility of Post-hoc Path-Specific Fairness Audits

    Aug 3, 2026Nitish Nagesh, Elahe Khatibi, Thomas Dean Hughes +3Algorithmic AuditingAlgorithmic Fairness

    Department of Computer Science, University of California, Irvine, Irvine, CA, USA · University of Orléans, Orléans, France

  5. AutoCause: A Python framework that automates expert decisions in environmental time-series causal discovery

    Jul 31, 2026Marco Ruiz, Miguel Arana-Catania, David R. Ardila +1Time-Series Causal DiscoveryCausal Discovery

    ISR-Lisbon, Instituto Superior Técnico, Av. Rovisco Pais 1, Lisbon, 1049-001, Portugal · Digital Scholarship at Oxford, University of Oxford, Oxford, OX1 3BG, United Kingdom · Jet Propulsion Lab., Caltech, Pasadena, CA 91109, California, USA

  6. Evidence-Type Competition: When Can Interventional Data Teach Language Models Causal Direction?

    Jul 31, 2026Xining XunCausal DiscoveryCausal Reasoning in Language Models

    Tsingjiao Information Science (Beijing) Co., Ltd.

  7. Causal Discovery with Inverted Self-attention for Multivariate Time Series

    Jul 30, 2026Yusen Liu, Yong Wang, Yifan Yin +3Time-Series Causal DiscoveryCausal Discovery

    School of Computer Science, University of Technology Sydney, Sydney, Australia · TianFu YongXing Laboratory, Chengdu, China · Faculty of Data Science, City University of Macau, Macau, China +1

  8. EvoCause: LLM-Guided Evolution of Causal Graphs for Root Cause Analysis

    Jul 29, 2026Lei Zan, Keli Zhang, Shifeng Xie +7Causal DiscoveryRoot Cause Analysis

    Huawei Noah’s Ark Lab · Guangdong University of Technology, Peng Cheng Laboratory

  9. Causal-TS: A Python Library for Causal Discovery in High-Dimensional and Nonstationary Time Series

    Jul 27, 2026Mohammad FesangharyTime-Series Causal DiscoveryCausal Discovery

    Bloomberg LP, New York, NY, USA

  10. Amortized Bayesian Causal Discovery of Extended Factor Graphs

    Jul 24, 2026Yichen Gu, Yuxuan Song, Weizhou Qian +2Causal DiscoveryProbabilistic Graphical Models

    Department of Electrical and Computer Engineering University of Michigan Ann Arbor, MI 48109, USA · Department of Computational Medicine and Bioinformatics University of Michigan, Ann Arbor Ann Arbor, MI 48109, USA · Department of Statistics University of Michigan, Ann Arbor Ann Arbor, MI 48109, USA +1

  11. CEDAR: Causal Edge Discovery for Autoregressive Processes

    Jul 22, 2026Mohammad FesangharyTime-Series Causal DiscoveryCausal Discovery

    Bloomberg LP

  12. Local Causal Structure Learning in the Presence of Latent Variables and Selection Bias

    Jul 22, 2026Zheng Li, Hao Zhang, Ruxin Wang +3Causal DiscoveryCausal Structure Learning

    Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China. · School of Computer Science, Guangdong University of Technology, Guangzhou, China. · Peng Cheng Laboratory, Shenzhen, China. +3

  13. Causal Discovery on Irregular Time Series

    Jul 20, 2026Martim Penim, Ricardo Ribeiro Pereira, Jacopo Bono +3Irregular Time-Series ModelingTime-Series Causal Discovery

    1Feedzai, Portugal · 3DCC, Faculdade de Ciêncidas da Universidade do Porto, Portugal · 2Instituto Superior Técnico, Universidade de Lisboa, Portugal +1

  14. Falsifying Causal Graphs With Outlier Events

    Jul 13, 2026William Roy Orchard, Philipp M. Faller, Dominik JanzingCausal DiscoveryStatistical Hypothesis Testing

    University of Cambridge, Cambridge, UK · Karlsruhe Institute of Technology, Karlsruhe, Germany · Amazon Research, Tübingen, Germany

  15. Relaxing Faithfulness with Intervention-Only Causal Discovery

    Jul 13, 2026Bijan Mazaheri, Jiaqi Zhang, Caroline UhlerCausal DiscoveryCausal Identifiability

    Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire, USA · Schmidt Center, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA · Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

  16. DAG-FM: A Foundation Model for Causal Discovery under Heterogeneous Causal Mechanisms

    Jul 13, 2026Yikang Chen, Zhengkang Guan, Haoyuan Qian +3Causal Foundation ModelsTabular Foundation Models

    1Zhejiang University · 2Tsinghua University

  17. CDFM: Towards a General-Purpose Causal Discovery Foundation Model

    Jul 13, 2026Jie Qiao, Ruichu Cai, Zijian Li +6Causal Foundation ModelsCausal Discovery

    School of Computer Science, Guangdong University of Technology, Guangzhou, China · College of Mathematics and Computer, Shantou University, Shantou, China · Department of Computer Science and Technology, Tsinghua University, Beijing, China

  18. Integrating Background Knowledge for Scalable Causal Discovery

    Jul 11, 2026Mátyás Schubert, Theofanis Aslanidis, Tom Claassen +1Causal DiscoveryCausal Structure Learning

    University of Amsterdam · Radboud University Nijmegen · Saarland University

  19. How Does Bayesian Causal Discovery Fail? Characterising Structural Consequences in Linear Gaussian Networks under Latent Confounding

    Jul 10, 2026Debargha Ghosh, Silja Renooij, Anna V. KononovaStructural Causal ModelsBayesian Networks

    Department of Information and Computing Sciences, Utrecht University · Leiden Institute of Advanced Computer Science, Leiden University

  20. DKCD: Domain Knowledge-Enhanced Causal Discovery from Unstructured Data

    Jul 10, 2026Xin Li, Jin Li, Shoujin Wang +2Causal DiscoveryCausal Structure Learning

    University of Technology Sydney · Sydney, NSW, Australia

  21. Learning Sparsest Linear Causal DAGs with Latent Confounders via Higher-Order Cumulants

    Jul 7, 2026Ming Cai, Hisayuki HaraStructural Causal ModelsCausal Discovery

    Graduate School of Informatics, Kyoto University, Kyoto, Japan · Institute for Liberal Arts and Sciences, Kyoto University, Kyoto, Japan

  22. Causal ASCEND: Scalable Two-tier Causal Discovery on High Dimensional Multi-omics Data

    Jul 5, 2026Stephen Asiedu, David WatsonCausal DiscoveryGene Regulatory Network Inference

    Department of Informatics, King’s College London, Bush House, 30 Aldwych, WC2B 4BG, London, United Kingdom

  23. Knowledge-Informed Local Causal Discovery of Optimal Adjustment Sets

    Jul 5, 2026Seong Woo Ahn, Alessandro Leite, José Lucas De Melo Costa +3Causal Effect EstimationCausal Discovery

    Laboratoire Interdisciplinaire des Sciences du Numérique, Université Paris-Saclay, CNRS, CentraleSupélec, France · LITIS UR 4108, INSA Rouen Normandy, University of Rouen Normandy, France

  24. MDL Meets Latent Confounders: LNML-based Causal Discovery

    Jul 5, 2026Zhongyi Que, Shin Matsushima, Kenji YamanishiMinimum Description LengthCausal Discovery

    Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan · Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan

  25. Order-based Causal Discovery for Multistage Processes

    Jul 4, 2026Eun-Yeol Ma, Junsub Jung, Heeyoung KimCausal Discovery

    Department of Industrial and Systems Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, South Korea

  26. Statistically Meaningful Geometry and Gauge Symmetry Breaking: A Geometric Foundation for Scientific Discovery and Intelligence Emergence

    Jul 3, 2026Bing Cheng, Yi-Shuai Niu, Howell Tong +1AI for ScienceCausal Discovery

    Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China · Beijing Institute of Mathematical Sciences and Applications (BIMSA), Beijing, China · Department of Statistics, London School of Economics and Political Science, London WC2A 2AE, UK +3

  27. CausalSteward: An Agentic Divide-Conquer-Combine Copilot for Causal Discovery

    Jul 2, 2026Nicholas Tagliapietra, Gian Lorenzo Marchioni, Moritz Willig +3Causal DiscoveryMulti-Agent Collaboration

    1 : Computer Science Department, TU Darmstadt, Germany · 2 : Bosch Center for Artificial Intelligence, Renningen, Germany · 5 : LUISS University, Rome, Italy +2

  28. A Neuroimaging Simulation Framework for Developing and Evaluating Causal AI

    Jun 27, 2026Eryn Libert-Scott, Emma A. M. Stanley, Vibujithan Vigneshwaran +3Image GenerationCausal Discovery

    Biomedical Engineering Graduate Program, University of Calgary, Calgary, AB, Canada · Department of Radiology, the Hotchkiss Brain Institute, the Alberta Children’s Hospital Research Institute, and Department of Clinical Neuroscience, all at the University of Calgary, Calgary, Alberta, Canada · Department of Computing, Imperial College London, London, U.K. +1

  29. RetiSEM: Generalising Causal Models for Fragmented Biomedical Data

    Jun 23, 2026Inam Ullah, Imran Razzak, Shoaib JameelLatent Variable ModelsStructural Causal Models

    University of Southampton, Southampton, SO18 1PB, Hampshir, United Kingdom · Mohamed bin Zayed University of Artificial Intelligence, United Arab Emirates

  30. GRACE: Gated Refinement for Accurate Causal Edge Discovery in High-Dimensional Time Series

    Jun 22, 2026Mohammad Fesanghary, Abhinav HavaldarTime-Series Causal DiscoveryCausal Discovery