Chandler Squires
16 papers · 2018–2025 · 5 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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πΊοΈ Taxonomy Completionist (24) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Gold π£ Hot Topic Early Bird
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Deep Specialist
(14)
π€
Dynamic Duo
(13)
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Century Club Β· Bronze
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Trend Setter
π
Conference Pioneer
ποΈ
Keyword Collector
(64)
π₯
Unstoppable Β· Bronze
Top co-authors
Research topics
Artificial Intelligence
(14)
Core AI
(14)
Machine Learning
(10)
Knowledge & Reasoning
(9)
Reasoning
(9)
Mathematics & Optimization
(4)
Core Methods
(4)
Learning Types
(4)
Optimization & Theory
(3)
Bayesian & Probabilistic
(2)
Learning Paradigms
(2)
Mathematics
(2)
Deep Learning
(1)
Interdisciplinary
(1)
Application Areas
(1)
Keywords
causal inference
(7)
causal discovery
(6)
latent variable
(4)
directed acyclic graph
(4)
causal graph
(3)
latent factor model
(3)
interventional data
(3)
structure learning
(2)
causal imputation
(2)
causal disentanglement
(2)
gene regulatory network
(2)
markov equivalence class
(2)
causal structure
(2)
causal model
(2)
causal dag
(2)
gene expression
(1)
structural learning
(1)
causal structure learning
(1)
high-dimensional inference
(1)
causal reasoning
(1)
Papers
Probably approximately correct high-dimensional causal effect estimation given a valid adjustment set
CLeaR 2025
Synthetic Potential Outcomes and Causal Mixture Identifiability
AISTATS 2025
The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications
CLeaR 2025
Causal Imputation for Counterfactual SCMs: Bridging Graphs and Latent Factor Models
CLeaR 2024
Identifiability Guarantees for Causal Disentanglement from Soft Interventions
NeurIPS 2023
Linear Causal Disentanglement via Interventions
ICML 2023
Unpaired Multi-Domain Causal Representation Learning
NeurIPS 2023
Causal Imputation via Synthetic Interventions
CLeaR 2022
Causal Structure Discovery between Clusters of Nodes Induced by Latent Factors
CLeaR 2022
Matching a Desired Causal State via Shift Interventions
NeurIPS 2021
Active Structure Learning of Causal DAGs via Directed Clique Trees
NeurIPS 2020
Ordering-Based Causal Structure Learning in the Presence of Latent Variables
AISTATS 2020
Permutation-Based Causal Structure Learning with Unknown Intervention Targets
UAI 2020
ABCD-Strategy: Budgeted Experimental Design for Targeted Causal Structure Discovery
AISTATS 2019
Size of Interventional Markov Equivalence Classes in random DAG models
AISTATS 2019
Direct Estimation of Differences in Causal Graphs
NeurIPS 2018