Peter Spirtes
27 papers · 2001–2025 · 7 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (28) π Academic Marathon Β· Ultra π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Deep Specialist
(20)
π€
Dynamic Duo
(14)
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Triple Crown
π§¬
Topic Evolution
π
Keyword Champion
(2)
π§
Keyword Pioneer
π
Trend Setter
π₯
Unstoppable Β· Bronze
β‘
Prolific Year Β· Productive
ποΈ
Keyword Collector
(112)
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Renaissance Researcher
(7)
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Century Club Β· Bronze
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Conference Pioneer
Top co-authors
Research topics
Artificial Intelligence
(22)
Core AI
(22)
Machine Learning
(17)
Knowledge & Reasoning
(15)
Reasoning
(15)
Optimization & Theory
(9)
Learning Types
(7)
Core Methods
(6)
Mathematics & Optimization
(3)
Bayesian & Probabilistic Β· Machine Learning
(3)
Application Areas
(2)
Bayesian & Probabilistic Β· Artificial Intelligence
(2)
Mathematics
(2)
Representation
(2)
Data Science & Analytics
(1)
Keywords
causal discovery
(9)
latent variable
(7)
causal inference
(7)
graphical model
(5)
structure learning
(4)
directed acyclic graph
(4)
ancestral graph
(2)
causal effect estimation
(2)
additive noise model
(2)
equivalence class
(2)
observational data
(2)
causal structure
(2)
causal structure learning
(2)
causal graphical model
(2)
linear non-gaussian model
(2)
conditional independence
(2)
causal effect
(2)
selection bia
(2)
markov equivalence class
(2)
independence testing
(1)
Papers
Causal Representation Learning from General Environments under Nonparametric Mixing
AISTATS 2025
Latent Variable Causal Discovery under Selection Bias
ICML 2025
Permutation-based Rank Test in the Presence of Discretization and Application in Causal Discovery with Mixed Data
ICML 2025
Prompting Fairness: Integrating Causality to Debias Large Language Models
ICLR 2025
Reflection-Window Decoding: Text Generation with Selective Refinement
ICML 2025
Selecting Accurate Subgraphical Models from Possibly Inaccurate Graphical Models
CLeaR 2025
When Selection Meets Intervention: Additional Complexities in Causal Discovery
ICLR 2025
A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables
ICLR 2024
Causal-learn: Causal Discovery in Python
JMLR 2024
Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View
ICLR 2024
Identifying Latent State-Transition Processes for Individualized Reinforcement Learning
NeurIPS 2024
On the Parameter Identifiability of Partially Observed Linear Causal Models
NeurIPS 2024
Procedural Fairness Through Decoupling Objectionable Data Generating Components
ICLR 2024
Score-Based Causal Discovery of Latent Variable Causal Models
ICML 2024
A Uniformly Consistent Estimator of non-Gaussian Causal Effects Under the k-Triangle-Faithfulness Assumption
CLeaR 2022
Independence Testing-Based Approach to Causal Discovery under Measurement Error and Linear Non-Gaussian Models
NeurIPS 2022
On the Completeness of Causal Discovery in the Presence of Latent Confounding with Tiered Background Knowledge
AISTATS 2020
Learning the Structure of a Nonstationary Vector Autoregression
AISTATS 2019
A Hybrid Causal Search Algorithm for Latent Variable Models
PGM 2016
Estimating Causal Effects with Ancestral Graph Markov Models
PGM 2016
Data-driven covariate selection for nonparametric estimation of causal effects
AISTATS 2013
Statistical test for consistent estimation of causal effects in linear non-Gaussian models
AISTATS 2012
Learning equivalence classes of acyclic models with latent and selection variables from multiple datasets with overlapping variables
AISTATS 2011
Introduction to Causal Inference
JMLR 2010
Nonlinear directed acyclic structure learning with weakly additive noise models
NeurIPS 2009
Learning the Structure of Linear Latent Variable Models
JMLR 2006
Design and Analysis of the Causation and Prediction Challenge
AISTATS 2001