Clark Glymour
15 papers · 2006–2024 · 5 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π Conference Polyglot (5) π Interdisciplinary Bridge π§ Keyword Pioneer π Academic Marathon (18)
π£
Hot Topic Early Bird
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Renaissance Researcher
(6)
π
Conference Polyglot
(5)
π€
Dynamic Duo
(12)
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Keyword Champion
(3)
π¬
Deep Specialist
(12)
ποΈ
Keyword Collector
(76)
π
Trend Setter
π
Century Club
(15)
Conferences
NIPS (6)
JMLR (4)
ICML (3)
AAAI (1)
IJCAI (1)
Top co-authors
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