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Clark Glymour

15 papers · 2006–2024 · 5 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (18) 🐝 Cross-Pollinator (13) πŸ—ΊοΈ Taxonomy Completionist (26) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (6) 🌍 Conference Polyglot (5) 🀝 Dynamic Duo (12) πŸ† Keyword Champion (3) πŸ”¬ Deep Specialist (12) πŸ—ƒοΈ Keyword Collector (76) πŸ“ˆ Trend Setter πŸ’Ž Century Club (15)

Conferences

NIPS (6) JMLR (4) ICML (3) AAAI (1) IJCAI (1)

Top co-authors

Kun Zhang (12) Biwei Huang (10) Mingming Gong (5) Feng Xie (4) Bernhard SchΓΆlkopf (4) Ruichu Cai (3) Zhifeng Hao (2) Jiji Zhang (2) Chaochao Lu (1) Zhi Geng (1)

Keywords

causal discovery (12) causal structure (5) causal inference (4) latent variable (4) graphical model (3) structural learning (2) nonstationary datum (2) causal orientation (2) independent noise (2) domain adaptation (2) structural equation model (2) structure learning (1) maximum likelihood (1) covariate shift (1) causal structure learning (1) bayesian inference (1) policy learning (1) distributed data (1) distributed learning (1) distribution shift (1)

Papers

Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables JMLR 2024
Latent Hierarchical Causal Structure Discovery with Rank Constraints NIPS 2022
Action-Sufficient State Representation Learning for Control with Structural Constraints ICML 2022
Causal Discovery from Multiple Data Sets with Non-Identical Variable Sets AAAI 2020
Causal Discovery from Heterogeneous/Nonstationary Data JMLR 2020
Domain Adaptation as a Problem of Inference on Graphical Models NIPS 2020
Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs NIPS 2020
Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering NIPS 2019
Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models ICML 2019
Triad Constraints for Learning Causal Structure of Latent Variables NIPS 2019
Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination IJCAI 2017
Domain Adaptation with Conditional Transferable Components ICML 2016
Search for Additive Nonlinear Time Series Causal Models JMLR 2008
Integrating Locally Learned Causal Structures with Overlapping Variables NIPS 2008
Learning the Structure of Linear Latent Variable Models JMLR 2006