Peter Spirtes

26 papers · 2006–2025 · 7 conferences · across top CS/AI conferences

Achievements

+14 more ↓

🐣 Hot Topic Early Bird 🌍 Conference Polyglot (7) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🏃 Academic Marathon (19)

🐝 Cross-Pollinator (14) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🤝 Dynamic Duo (14) 👑 Triple Crown 🔬 Deep Specialist (13) 🧬 Topic Evolution 🏆 Keyword Champion 🚀 Conference Pioneer 🗃️ Keyword Collector (67) ⚡ Prolific Year (7) 💎 Century Club (26) 🔥 Unstoppable (5) 📈 Trend Setter

Conferences

AISTATS (6) ICLR (5) ICML (4) NIPS (4) JMLR (3) CLEAR (2) PGM (2)

Top co-authors

Kun Zhang (14) Xinshuai Dong (8) Ignavier Ng (8) Haoyue Dai (6) Biwei Huang (5) Zeyu Tang (4) Roberto Legaspi (3) Songyao Jin (3) Yang Liu (2) Yujia Zheng (2)

Keywords

causal inference (6) causal discovery (6) graphical model (5) latent variable (4) directed acyclic graph (3) structure learning (3) causal structure learning (2) linear non-gaussian model (2) causal effect estimation (2) ancestral graph (2) observational datum (2) causal effect (2) nonlinear structure learning (1) regression analysis (1) independence testing (1) conditional dependence (1) graph structure (1) causal structure (1) latent variable model (1) nonparametric estimation (1)

Papers

Latent Variable Causal Discovery under Selection Bias ICML 2025 Reflection-Window Decoding: Text Generation with Selective Refinement ICML 2025 Permutation-based Rank Test in the Presence of Discretization and Application in Causal Discovery with Mixed Data ICML 2025 Causal Representation Learning from General Environments under Nonparametric Mixing AISTATS 2025 Selecting Accurate Subgraphical Models from Possibly Inaccurate Graphical Models CLEAR 2025 Prompting Fairness: Integrating Causality to Debias Large Language Models ICLR 2025 When Selection Meets Intervention: Additional Complexities in Causal Discovery ICLR 2025 Identifying Latent State-Transition Processes for Individualized Reinforcement Learning NIPS 2024 Causal-learn: Causal Discovery in Python JMLR 2024 Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View ICLR 2024 Procedural Fairness Through Decoupling Objectionable Data Generating Components ICLR 2024 Score-Based Causal Discovery of Latent Variable Causal Models ICML 2024 A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables ICLR 2024 On the Parameter Identifiability of Partially Observed Linear Causal Models NIPS 2024 Independence Testing-Based Approach to Causal Discovery under Measurement Error and Linear Non-Gaussian Models NIPS 2022 A Uniformly Consistent Estimator of non-Gaussian Causal Effects Under the $k$-Triangle-Faithfulness Assumption CLEAR 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 NIPS 2009 Learning the Structure of Linear Latent Variable Models JMLR 2006