Peter Spirtes - RankMe

115 papers A* 13A 26B 2Journal 60Unranked 12

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Distributional Equivalence in Linear Non-Gaussian Latent-Variable Cyclic Causal Models: Characterization and Learning. CoRR Haoyue Dai, Immanuel Albrecht, Peter Spirtes, Kun Zhang
2025	J	`jnl`	Algorithmic Fairness amid Social Determinants: Reflection, Characterization, and Approach. CoRR Zeyu Tang, Alex John London, Atoosa Kasirzadeh, Sanmi Koyejo, Peter Spirtes, Kun Zhang
2025	J	`jnl`	Causal Discovery and Counterfactual Reasoning to Optimize Persuasive Dialogue Policies. CoRR Donghuo Zeng, Roberto Legaspi, Yuewen Sun, Xinshuai Dong, Kazushi Ikeda, Peter Spirtes, Kun Zhang
2025	A	`conf`	Causal Representation Learning from General Environments under Nonparametric Mixing. AISTATS Ignavier Ng, Shaoan Xie, Xinshuai Dong, Peter Spirtes, Kun Zhang
2025	J	`jnl`	Corrigendum to "Estimating bounds on causal effects in high-dimensional and possibly confounded systems" [Int. J. Approx. Reason. 88 (2017) 371-384]. Int. J. Approx. Reason. Daniel Malinsky, Peter Spirtes
2025	A	`conf`	Generative Framework for Personalized Persuasion: Inferring Causal, Counterfactual, and Latent Knowledge. UMAP Donghuo Zeng, Roberto Legaspi, Yuewen Sun, Xinshuai Dong, Kazushi Ikeda, Peter Spirtes, Kun Zhang
2025	J	`jnl`	Generative Framework for Personalized Persuasion: Inferring Causal, Counterfactual, and Latent Knowledge. CoRR Donghuo Zeng, Roberto Legaspi, Yuewen Sun, Xinshuai Dong, Kazushi Ikeda, Peter Spirtes, Kun Zhang
2025	A*	`conf`	Latent Variable Causal Discovery under Selection Bias. ICML Haoyue Dai, Yiwen Qiu, Ignavier Ng, Xinshuai Dong, Peter Spirtes, Kun Zhang
2025	J	`jnl`	Latent Variable Causal Discovery under Selection Bias. CoRR Haoyue Dai, Yiwen Qiu, Ignavier Ng, Xinshuai Dong, Peter Spirtes, Kun Zhang
2025	B	`conf`	Learning Hidden Causal Factors from Psychometrics Data Using Distributional Information. CogSci Roberto Legaspi, Xinshuai Dong, Donghuo Zeng, Yuewen Sun, Kazushi Ikeda, Peter Spirtes, Kun Zhang
2025	J	`jnl`	Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challenges. Trans. Mach. Learn. Res. Usman Gohar, Zeyu Tang, Jialu Wang, Kun Zhang, Peter Spirtes, Yang Liu, Lu Cheng
2025	J	`jnl`	Permutation-Based Rank Test in the Presence of Discretization and Application in Causal Discovery with Mixed Data. CoRR Xinshuai Dong, Ignavier Ng, Boyang Sun, Haoyue Dai, Guang-Yuan Hao, Shunxing Fan, Peter Spirtes, Yumou Qiu, Kun Zhang
2025	A*	`conf`	Permutation-based Rank Test in the Presence of Discretization and Application in Causal Discovery with Mixed Data. ICML Xinshuai Dong, Ignavier Ng, Boyang Sun, Haoyue Dai, Guang-Yuan Hao, Shunxing Fan, Peter Spirtes, Yumou Qiu, Kun Zhang
2025	J	`jnl`	PersonaX: Multimodal Datasets with LLM-Inferred Behavior Traits. CoRR Loka Li, Wong Yu Kang, Minghao Fu, Guangyi Chen, Zhenhao Chen, Gongxu Luo, Yuewen Sun, Salman H. Khan, Peter Spirtes, Kun Zhang
2025	A*	`conf`	Prompting Fairness: Integrating Causality to Debias Large Language Models. ICLR Jingling Li, Zeyu Tang, Xiaoyu Liu, Peter Spirtes, Kun Zhang, Liu Leqi, Yang Liu
2025	A*	`conf`	Reflection-Window Decoding: Text Generation with Selective Refinement. ICML Zeyu Tang, Zhenhao Chen, Xiangchen Song, Loka Li, Yunlong Deng, Yifan Shen, Guangyi Chen, Peter Spirtes, Kun Zhang
2025	J	`jnl`	Reflection-Window Decoding: Text Generation with Selective Refinement. CoRR Zeyu Tang, Zhenhao Chen, Loka Li, Xiangchen Song, Yunlong Deng, Yifan Shen, Guangyi Chen, Peter Spirtes, Kun Zhang
2025	J	`jnl`	Score-based Greedy Search for Structure Identification of Partially Observed Linear Causal Models. CoRR Xinshuai Dong, Ignavier Ng, Haoyue Dai, Jiaqi Sun, Xiangchen Song, Peter Spirtes, Kun Zhang
2025	—	`conf`	Selecting Accurate Subgraphical Models from Possibly Inaccurate Graphical Models. CLeaR Yi Han, Joseph D. Ramsey, Peter Spirtes
2025	A*	`conf`	When Selection Meets Intervention: Additional Complexities in Causal Discovery. ICLR Haoyue Dai, Ignavier Ng, Jianle Sun, Zeyu Tang, Gongxu Luo, Xinshuai Dong, Peter Spirtes, Kun Zhang
2025	J	`jnl`	When Selection Meets Intervention: Additional Complexities in Causal Discovery. CoRR Haoyue Dai, Ignavier Ng, Jianle Sun, Zeyu Tang, Gongxu Luo, Xinshuai Dong, Peter Spirtes, Kun Zhang
2024	A*	`conf`	A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables. ICLR Xinshuai Dong, Biwei Huang, Ignavier Ng, Xiangchen Song, Yujia Zheng, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang
2024	J	`jnl`	Causal-learn: Causal Discovery in Python. J. Mach. Learn. Res. Yujia Zheng, Biwei Huang, Wei Chen, Joseph D. Ramsey, Mingming Gong, Ruichu Cai, Shohei Shimizu, Peter Spirtes, Kun Zhang
2024	J	`jnl`	Choosing DAG Models Using Markov and Minimal Edge Count in the Absence of Ground Truth. CoRR Joseph D. Ramsey, Bryan Andrews, Peter Spirtes
2024	B	`conf`	Counterfactual Reasoning Using Predicted Latent Personality Dimensions for Optimizing Persuasion Outcome. PERSUASIVE Donghuo Zeng, Roberto Sebastian Legaspi, Yuewen Sun, Xinshuai Dong, Kazushi Ikeda, Peter Spirtes, Kun Zhang
2024	J	`jnl`	Counterfactual Reasoning Using Predicted Latent Personality Dimensions for Optimizing Persuasion Outcome. CoRR Donghuo Zeng, Roberto Legaspi, Yuewen Sun, Xinshuai Dong, Kazushi Ikeda, Peter Spirtes, Kun Zhang
2024	A*	`conf`	Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View. ICLR Haoyue Dai, Ignavier Ng, Gongxu Luo, Peter Spirtes, Petar Stojanov, Kun Zhang
2024	J	`jnl`	Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View. CoRR Haoyue Dai, Ignavier Ng, Gongxu Luo, Peter Spirtes, Petar Stojanov, Kun Zhang
2024	J	`jnl`	IEEE Transactions on Neural Networks and Learning Systems Special Issue on Causal Discovery and Causality-Inspired Machine Learning. IEEE Trans. Neural Networks Learn. Syst. Kun Zhang, Ilya Shpitser, Sara Magliacane, Davide Bacciu, Fei Wu, Changshui Zhang, Peter Spirtes
2024	A*	`conf`	Identifying Latent State-Transition Processes for Individualized Reinforcement Learning. NeurIPS Yuewen Sun, Biwei Huang, Yu Yao, Donghuo Zeng, Xinshuai Dong, Songyao Jin, Boyang Sun, Roberto Legaspi, Kazushi Ikeda, Peter Spirtes, Kun Zhang
2024	A*	`conf`	On the Parameter Identifiability of Partially Observed Linear Causal Models. NeurIPS Xinshuai Dong, Ignavier Ng, Biwei Huang, Yuewen Sun, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang
2024	J	`jnl`	On the Parameter Identifiability of Partially Observed Linear Causal Models. CoRR Xinshuai Dong, Ignavier Ng, Biwei Huang, Yuewen Sun, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang
2024	A*	`conf`	Procedural Fairness Through Decoupling Objectionable Data Generating Components. ICLR Zeyu Tang, Jialu Wang, Yang Liu, Peter Spirtes, Kun Zhang
2024	A*	`conf`	Score-Based Causal Discovery of Latent Variable Causal Models. ICML Ignavier Ng, Xinshuai Dong, Haoyue Dai, Biwei Huang, Peter Spirtes, Kun Zhang
2024	J	`jnl`	Steering LLMs Towards Unbiased Responses: A Causality-Guided Debiasing Framework. CoRR Jingling Li, Zeyu Tang, Xiaoyu Liu, Peter Spirtes, Kun Zhang, Liu Leqi, Yang Liu
2023	J	`jnl`	A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables. CoRR Xinshuai Dong, Biwei Huang, Ignavier Ng, Xiangchen Song, Yujia Zheng, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang
2023	J	`jnl`	Causal-learn: Causal Discovery in Python. CoRR Yujia Zheng, Biwei Huang, Wei Chen, Joseph D. Ramsey, Mingming Gong, Ruichu Cai, Shohei Shimizu, Peter Spirtes, Kun Zhang
2023	J	`jnl`	Editorial Special Issue on Causality: Fundamental Limits and Applications. IEEE J. Sel. Areas Inf. Theory Negar Kiyavash, Elias Bareinboim, Todd P. Coleman, Alex Dimakis, Bernhard Schlkopf, Peter Spirtes, Kun Zhang, Robert Nowak
2023	J	`jnl`	Procedural Fairness Through Decoupling Objectionable Data Generating Components. CoRR Zeyu Tang, Jialu Wang, Yang Liu, Peter Spirtes, Kun Zhang
2022	—	`conf`	A Uniformly Consistent Estimator of non-Gaussian Causal Effects Under the k-Triangle-Faithfulness Assumption. CLeaR Shuyan Wang, Peter Spirtes
2022	A*	`conf`	Independence Testing-Based Approach to Causal Discovery under Measurement Error and Linear Non-Gaussian Models. NeurIPS Haoyue Dai, Peter Spirtes, Kun Zhang
2022	J	`jnl`	Independence Testing-Based Approach to Causal Discovery under Measurement Error and Linear Non-Gaussian Models. CoRR Haoyue Dai, Peter Spirtes, Kun Zhang
2022	J	`jnl`	The m-connecting imset and factorization for ADMG models. CoRR Bryan Andrews, Gregory F. Cooper, Thomas S. Richardson, Peter Spirtes
2021	J	`jnl`	A Uniformly Consistent Estimator of non-Gaussian Causal Effects Under the k-Triangle-Faithfulness Assumption. CoRR Shuyan Wang, Peter Spirtes
2020	J	`jnl`	Learning from Positive and Unlabeled Data by Identifying the Annotation Process. CoRR Naji Shajarisales, Peter Spirtes, Kun Zhang
2019	A	`conf`	Learning the Structure of a Nonstationary Vector Autoregression. AISTATS Daniel Malinsky, Peter Spirtes
2019	J	`jnl`	Mixed graphical models for integrative causal analysis with application to chronic lung disease diagnosis and prognosis. Bioinform. Andrew J. Sedgewick, Kristina Buschur, Ivy Shi, Joseph D. Ramsey, Vineet K. Raghu, Dimitris V. Manatakis, Yingze Zhang, Jessica Bon, Divay Chandra, Chad Karoleski, Frank C. Sciurba, Peter Spirtes, Clark Glymour, Panayiotis V. Benos
2018	A	`conf`	Causal Discovery with Linear Non-Gaussian Models under Measurement Error: Structural Identifiability Results. UAI Kun Zhang, Mingming Gong, Joseph D. Ramsey, Kayhan Batmanghelich, Peter Spirtes, Clark Glymour
2018	—	`conf`	Causal Structure Learning from Multivariate Time Series in Settings with Unmeasured Confounding. CD@KDD Daniel Malinsky, Peter Spirtes
2018	J	`jnl`	Comparison of strategies for scalable causal discovery of latent variable models from mixed data. Int. J. Data Sci. Anal. Vineet K. Raghu, Joseph D. Ramsey, Alison Morris, Dimitrios V. Manatakis, Peter Spirtes, Panos K. Chrysanthis, Clark Glymour, Panayiotis V. Benos
2017	J	`jnl`	Causal Discovery in the Presence of Measurement Error: Identifiability Conditions. CoRR Kun Zhang, Mingming Gong, Joseph D. Ramsey, Kayhan Batmanghelich, Peter Spirtes, Clark Glymour
2017	—	`conf`	Discovery of Causal Models that Contain Latent Variables Through Bayesian Scoring of Independence Constraints. ECML/PKDD (2) Fattaneh Jabbari, Joseph D. Ramsey, Peter Spirtes, Gregory F. Cooper
2017	J	`jnl`	Estimating bounds on causal effects in high-dimensional and possibly confounded systems. Int. J. Approx. Reason. Daniel Malinsky, Peter Spirtes
2017	—	`conf`	Methods to Expand Cell Signaling Models Using Automated Reading and Model Checking. CMSB Kai-Wen Liang, Qinsi Wang, Cheryl Telmer, Divyaa Ravichandran, Peter Spirtes, Natasa Miskov-Zivanov
2017	J	`jnl`	Mixed Graphical Models for Causal Analysis of Multi-modal Variables. CoRR Andrew J. Sedgewick, Joseph D. Ramsey, Peter Spirtes, Clark Glymour, Panayiotis V. Benos
2016	—	`conf`	A Hybrid Causal Search Algorithm for Latent Variable Models. Probabilistic Graphical Models Juan Miguel Ogarrio, Peter Spirtes, Joe Ramsey
2016	—	`conf`	Estimating Causal Effects with Ancestral Graph Markov Models. Probabilistic Graphical Models Daniel Malinsky, Peter Spirtes
2016	J	`jnl`	The three faces of faithfulness. Synth. Jiji Zhang, Peter Spirtes
2014	—	`conf`	Causal Clustering for 2-Factor Measurement Models. ECML/PKDD (2) Erich Kummerfeld, Joe Ramsey, Renjie Yang, Peter Spirtes, Richard Scheines
2013	A	`conf`	Calculation of Entailed Rank Constraints in Partially Non-Linear and Cyclic Models. UAI Peter Spirtes
2013	J	`jnl`	Calculation of Entailed Rank Constraints in Partially Non-Linear and Cyclic Models. CoRR Peter Spirtes
2013	J	`jnl`	Causal Inference in the Presence of Latent Variables and Selection Bias CoRR Peter Spirtes, Christopher Meek, Thomas S. Richardson
2013	A	`conf`	Data-driven covariate selection for nonparametric estimation of causal effects. AISTATS Doris Entner, Patrik O. Hoyer, Peter Spirtes
2013	J	`jnl`	Detecting Causal Relations in the Presence of Unmeasured Variables CoRR Peter Spirtes
2013	J	`jnl`	Directed Cyclic Graphical Representations of Feedback Models CoRR Peter Spirtes
2013	J	`jnl`	Semi-Instrumental Variables: A Test for Instrument Admissibility CoRR Tianjiao Chu, Richard Scheines, Peter Spirtes
2012	J	`jnl`	A Transformational Characterization of Markov Equivalence for Directed Acyclic Graphs with Latent Variables CoRR Jiji Zhang, Peter Spirtes
2012	J	`jnl`	A theoretical study of Y structures for causal discovery. CoRR Subramani Mani, Peter Spirtes, Gregory F. Cooper
2012	J	`jnl`	Adjacency-Faithfulness and Conservative Causal Inference. CoRR Joseph D. Ramsey, Jiji Zhang, Peter Spirtes
2012	J	`jnl`	Causal discovery of linear acyclic models with arbitrary distributions CoRR Patrik O. Hoyer, Aapo Hyvärinen, Richard Scheines, Peter Spirtes, Joseph D. Ramsey, Gustavo Lacerda, Shohei Shimizu
2012	J	`jnl`	Discovering Cyclic Causal Models by Independent Components Analysis CoRR Gustavo Lacerda, Peter Spirtes, Joseph D. Ramsey, Patrik O. Hoyer
2012	J	`jnl`	Learning Measurement Models for Unobserved Variables CoRR Ricardo Bezerra de Andrade e Silva, Richard Scheines, Clark Glymour, Peter Spirtes
2012	J	`jnl`	Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence (2010) CoRR Peter Grunwald, Peter Spirtes
2012	A	`conf`	Statistical test for consistent estimation of causal effects in linear non-Gaussian models. AISTATS Doris Entner, Patrik O. Hoyer, Peter Spirtes
2012	J	`jnl`	Strong Faithfulness and Uniform Consistency in Causal Inference CoRR Jiji Zhang, Peter Spirtes
2012	J	`jnl`	Towards Characterizing Markov Equivalence Classes for Directed Acyclic Graphs with Latent Variables CoRR Ayesha R. Ali, Thomas S. Richardson, Peter Spirtes, Jiji Zhang
2011	J	`jnl`	Intervention, determinism, and the causal minimality condition. Synth. Jiji Zhang, Peter Spirtes
2011	A	`conf`	Learning equivalence classes of acyclic models with latent and selection variables from multiple datasets with overlapping variables. AISTATS Robert E. Tillman, Peter Spirtes
2011	J	`jnl`	On meta-analyses of imaging data and the mixture of records. NeuroImage Joseph D. Ramsey, Peter Spirtes, Clark Glymour
2010	J	`jnl`	Actual causation: a stone soup essay. Synth. Clark Glymour, David Danks, Bruce Glymour, Frederick Eberhardt, Joseph D. Ramsey, Richard Scheines, Peter Spirtes, Choh Man Teng, Jiji Zhang
2010	J	`jnl`	Introduction to Causal Inference. J. Mach. Learn. Res. Peter Spirtes
2010	A	`ed.`	UAI 2010, Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence, Catalina Island, CA, USA, July 8-11, 2010 UAI Peter Grünwald, Peter Spirtes
2010	—	`conf`	When causality matters for prediction. NIPS Causality: Objectives and Assessment Robert E. Tillman, Peter Spirtes
2009	—	`conf`	Nonlinear directed acyclic structure learning with weakly additive noise models. NIPS Robert E. Tillman, Arthur Gretton, Peter Spirtes
2008	A	`conf`	Causal discovery of linear acyclic models with arbitrary distributions. UAI Patrik O. Hoyer, Aapo Hyvärinen, Richard Scheines, Peter Spirtes, Joseph D. Ramsey, Gustavo Lacerda, Shohei Shimizu
2008	—	`ed.`	Causation and Prediction Challenge at WCCI 2008, Hong Kong, June 1-6, 2008 WCCI Causation and Prediction Challenge Isabelle Guyon, Constantin F. Aliferis, Gregory F. Cooper, André Elisseeff, Jean-Philippe Pellet, Peter Spirtes, Alexander R. Statnikov
2008	—	`conf`	Design and Analysis of the Causation and Prediction Challenge. WCCI Causation and Prediction Challenge Isabelle Guyon, Constantin F. Aliferis, Gregory F. Cooper, André Elisseeff, Jean-Philippe Pellet, Peter Spirtes, Alexander R. Statnikov
2008	J	`jnl`	Detection of Unfaithfulness and Robust Causal Inference. Minds Mach. Jiji Zhang, Peter Spirtes
2008	A	`conf`	Discovering Cyclic Causal Models by Independent Components Analysis. UAI Gustavo Lacerda, Peter Spirtes, Joseph D. Ramsey, Patrik O. Hoyer
2008	J	`jnl`	Tabu Search-Enhanced Graphical Models for Classification in High Dimensions. INFORMS J. Comput. Xue Bai, Rema Padman, Joseph D. Ramsey, Peter Spirtes
2006	A	`conf`	A Theoretical Study of Y Structures for Causal Discovery. UAI Subramani Mani, Gregory F. Cooper, Peter Spirtes
2006	A	`conf`	Adjacency-Faithfulness and Conservative Causal Inference. UAI Joseph D. Ramsey, Jiji Zhang, Peter Spirtes
2006	—	`conf`	Graphical Models for the Identification of Causal Structures in Multivariate Time Series Models. JCIS Alessio Moneta, Peter Spirtes
2006	J	`jnl`	Learning the Structure of Linear Latent Variable Models. J. Mach. Learn. Res. Ricardo Bezerra de Andrade e Silva, Richard Scheines, Clark Glymour, Peter Spirtes
2005	A	`conf`	A Transformational Characterization of Markov Equivalence for Directed Acyclic Graphs with Latent Variables. UAI Jiji Zhang, Peter Spirtes
2005	A	`conf`	Towards Characterizing Markov Equivalence Classes for Directed Acyclic Graphs with Latent Variables. UAI Ayesha R. Ali, Thomas S. Richardson, Peter Spirtes, Jiji Zhang
2003	J	`jnl`	A Statistical Problem for Inference to Regulatory Structure from Associations of Gene Expression Measurements with Microarrays. Bioinform. Tianjiao Chu, Clark Glymour, Richard Scheines, Peter Spirtes
2003	A	`conf`	Learning Measurement Models for Unobserved Variables. UAI Ricardo Bezerra de Andrade e Silva, Richard Scheines, Clark Glymour, Peter Spirtes
2003	A	`conf`	Strong Faithfulness and Uniform Consistency in Causal Inference. UAI Jiji Zhang, Peter Spirtes
2002	J	`jnl`	Automated Remote Sensing with Near Infrared Reflectance Spectra: Carbonate Recognition. Data Min. Knowl. Discov. Joseph D. Ramsey, Paul Gazis, Ted Roush, Peter Spirtes, Clark Glymour
2001	A	`conf`	An Anytime Algorithm for Causal Inference. AISTATS Peter Spirtes
2001	A	`conf`	Semi-Instrumental Variables: A Test for Instrument Admissibility. UAI Tianjiao Chu, Richard Scheines, Peter Spirtes
2000	—	`book`	Causation, Prediction, and Search, Second Edition. Peter Spirtes, Clark Glymour, Richard Scheines
1999	A	`conf`	An experiment in causal discovery using a pneumona database. AISTATS Peter Spirtes, Gregory F. Cooper
1997	A	`conf`	A Note on Cyclic Graphs and Dynamical Feedback Systems. AISTATS Thomas S. Richardson, Peter Spirtes, Clark Glymour
1997	A	`conf`	A Polynomial Time Algorithm for Determining DAG Equivalence in the Presence of Latent Variables and Selection Bias. AISTATS Peter Spirtes, Thomas S. Richardson
1997	J	`jnl`	An evaluation of machine-learning methods for predicting pneumonia mortality. Artif. Intell. Medicine Gregory F. Cooper, Constantin F. Aliferis, Richard Ambrosino, John M. Aronis, Bruce G. Buchanan, Rich Caruana, Michael J. Fine, Clark Glymour, Geoffrey J. Gordon, Barbara H. Hanusa, Janine E. Janosky, Christopher Meek, Tom M. Mitchell, Thomas S. Richardson, Peter Spirtes
1997	A	`conf`	Heuristic Greedy Search Algorithms for Latent Variable Models. AISTATS Peter Spirtes, Thomas S. Richardson, Christopher Meek
1996	J	`jnl`	Vanishing TETRAD Differences and Model Structure. Int. J. Uncertain. Fuzziness Knowl. Based Syst. Glenn Shafer, Alexander Kogan, Peter Spirtes
1995	A	`conf`	Causal Inference in the Presence of Latent Variables and Selection Bias. UAI Peter Spirtes, Christopher Meek, Thomas S. Richardson
1995	A	`conf`	Directed Cyclic Graphical Representations of Feedback Models. UAI Peter Spirtes
1995	A*	`conf`	Learning Bayesian Networks with Discrete Variables from Data. KDD Peter Spirtes, Christopher Meek
1992	J	`jnl`	Finding latent variable models in large databases. Int. J. Intell. Syst. Richard Scheines, Peter Spirtes
1991	A	`conf`	Detecting Causal Relations in the Presence of Unmeasured Variables. UAI Peter Spirtes
1988	J	`jnl`	Treatment selection by constraint propagation a case study in cutting fluid selection. Artif. Intell. Eng. Des. Anal. Manuf. James E. Mogush, Dominique Carrega, Peter Spirtes, Mark S. Fox