Clark Glymour
15 papers · 2006–2024 · 5 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (22) 🏃 Academic Marathon · Full 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird
🧭
Keyword Pioneer
🤝
Dynamic Duo
(12)
🔬
Deep Specialist
(12)
🗃️
Keyword Collector
(75)
📈
Trend Setter
💎
Century Club · Bronze
Venues
Top co-authors
Research topics
Machine Learning
(13)
Artificial Intelligence
(12)
Core AI
(12)
Learning Types
(9)
Optimization & Theory
(6)
Knowledge & Reasoning
(5)
Reasoning
(5)
Bayesian & Probabilistic · Machine Learning
(3)
Core Methods
(3)
Data Science & Analytics
(2)
Application Areas
(2)
Bayesian & Probabilistic · Artificial Intelligence
(2)
Methods
(2)
Deep Learning
(1)
Reinforcement Learning
(1)
Keywords
causal discovery
(12)
causal structure
(5)
causal inference
(4)
latent variable
(4)
graphical model
(3)
structural learning
(2)
causal structure learning
(2)
independent noise
(2)
non-stationary data
(2)
domain adaptation
(2)
causal orientation
(2)
structural equation model
(2)
covariate shift
(1)
structure learning
(1)
maximum likelihood
(1)
bayesian inference
(1)
policy learning
(1)
non-stationary time series
(1)
distributed learning
(1)
distribution shift
(1)
Papers
Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables
JMLR 2024
Action-Sufficient State Representation Learning for Control with Structural Constraints
ICML 2022
Latent Hierarchical Causal Structure Discovery with Rank Constraints
NeurIPS 2022
Causal Discovery from Heterogeneous/Nonstationary Data
JMLR 2020
Causal Discovery from Multiple Data Sets with Non-Identical Variable Sets
AAAI 2020
Domain Adaptation as a Problem of Inference on Graphical Models
NeurIPS 2020
Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs
NeurIPS 2020
Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models
ICML 2019
Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering
NeurIPS 2019
Triad Constraints for Learning Causal Structure of Latent Variables
NeurIPS 2019
Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination
IJCAI 2017
Domain Adaptation with Conditional Transferable Components
ICML 2016
Integrating Locally Learned Causal Structures with Overlapping Variables
NeurIPS 2008
Search for Additive Nonlinear Time Series Causal Models
JMLR 2008
Learning the Structure of Linear Latent Variable Models
JMLR 2006