Ilya Shpitser
31 papers · 2008–2025 · 8 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer π Renaissance Researcher (5) π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (11) π£ Hot Topic Early Bird
π
Cross-Pollinator
(7)
πΊοΈ
Taxonomy Completionist
(11)
π§
Keyword Pioneer
πΊ
Lone Wolf
(3)
π
Keyword Champion
(2)
π¬
Deep Specialist
(20)
ποΈ
Keyword Collector
(91)
π
Conference Pioneer
π
Trend Setter
π
Century Club
(31)
π₯
Unstoppable
(8)
β‘
Prolific Year
(5)
Conferences
UAI (11)
AISTATS (5)
ICML (4)
JMLR (4)
NIPS (4)
CLEAR (1)
EMNLP (1)
PGM (1)
Top co-authors
Keywords
causal inference
(19)
graphical model
(10)
directed acyclic graph
(4)
causal discovery
(4)
missing datum
(4)
markov random field
(3)
measurement error
(3)
unmeasured confounding
(2)
hidden variable
(2)
semiparametric inference
(2)
treatment effect
(2)
causal graphical model
(2)
constrained optimization
(2)
structure learning
(2)
influence function
(2)
structural equation model
(2)
social network
(2)
bayesian network
(2)
inverse probability weighting
(2)
causal identification
(2)
Papers
Feature Importance Metrics in the Presence of Missing Data
ICML 2025
Evaluation of Active Feature Acquisition Methods for Time-varying Feature Settings
JMLR 2025
A General Identification Algorithm For Data Fusion Problems Under Systematic Selection
UAI 2024
Identification and Estimation for Nonignorable Missing Data: A Data Fusion Approach
ICML 2024
Zero Inflation as a Missing Data Problem: a Proxy-based Approach
UAI 2024
The Proximal ID Algorithm
JMLR 2023
The Lauritzen-Chen Likelihood For Graphical Models
AISTATS 2023
Optimal Training of Fair Predictive Models
CLEAR 2022
Causal Discovery in Linear Latent Variable Models Subject to Measurement Error
NIPS 2022
Semiparametric causal sufficient dimension reduction of multidimensional treatments
UAI 2022
Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal Inference
AISTATS 2022
Semiparametric Inference For Causal Effects In Graphical Models With Hidden Variables
JMLR 2022
Differentiable Causal Discovery Under Unmeasured Confounding
AISTATS 2021
Partial Identifiability in Discrete Data with Measurement Error
UAI 2021
Path dependent structural equation models
UAI 2021
Entropic Inequality Constraints from e-separation Relations in Directed Acyclic Graphs with Hidden Variables
UAI 2021
General Identification of Dynamic Treatment Regimes Under Interference
AISTATS 2020
Full Law Identification in Graphical Models of Missing Data: Completeness Results
ICML 2020
Identification and Estimation of Causal Effects Defined by Shift Interventions
UAI 2020
Deriving Bounds And Inequality Constraints Using Logical Relations Among Counterfactuals
UAI 2020
Intervening on Network Ties
UAI 2019
Causal Inference Under Interference And Network Uncertainty
UAI 2019
Identification In Missing Data Models Represented By Directed Acyclic Graphs
UAI 2019
A Potential Outcomes Calculus for Identifying Conditional Path-Specific Effects
AISTATS 2019
Learning Optimal Fair Policies
ICML 2019
Identification and Estimation of Causal Effects from Dependent Data
NIPS 2018
Structure Learning Under Missing Data
PGM 2018
Challenges of Using Text Classifiers for Causal Inference
EMNLP 2018
Consistent Estimation of Functions of Data Missing Non-Monotonically and Not at Random
NIPS 2016
Segregated Graphs and Marginals of Chain Graph Models
NIPS 2015
Complete Identification Methods for the Causal Hierarchy
JMLR 2008