AmirEmad Ghassami
15 papers · 2017–2024 · 7 conferences · across top CS/AI conferences
Achievements
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🏃 Academic Marathon (7) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (7) 🐝 Cross-Pollinator (7)
🌍
Conference Polyglot
(7)
🏃
Academic Marathon
(7)
🤝
Dynamic Duo
(11)
🔬
Deep Specialist
(12)
🧬
Topic Evolution
🚀
Conference Pioneer
💎
Century Club
(15)
🔥
Unstoppable
(8)
🗃️
Keyword Collector
(55)
Conferences
NIPS (5)
ICML (3)
JMLR (2)
UAI (2)
AAAI (1)
AISTATS (1)
CLEAR (1)
Top co-authors
Keywords
causal discovery
(7)
causal structure learning
(4)
causal inference
(4)
structure learning
(3)
experiment design
(2)
latent variable
(2)
markov equivalence
(2)
graphical model
(2)
structural causal model
(2)
directed acyclic graph
(2)
causal effect estimation
(1)
cycle detection
(1)
conditional mutual information
(1)
bayesian network
(1)
constraint optimization
(1)
causal structure
(1)
continuous optimization
(1)
structural equation model
(1)
gaussian graphical model
(1)
greedy algorithm
(1)
Papers
Identification and Estimation for Nonignorable Missing Data: A Data Fusion Approach
ICML 2024
A General Identification Algorithm For Data Fusion Problems Under Systematic Selection
UAI 2024
A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models
JMLR 2023
Causal Discovery in Linear Structural Causal Models with Deterministic Relations
CLEAR 2022
Causal Discovery in Linear Latent Variable Models Subject to Measurement Error
NIPS 2022
Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal Inference
AISTATS 2022
Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias
NIPS 2021
Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables
JMLR 2020
Model-Augmented Conditional Mutual Information Estimation for Feature Selection
UAI 2020
On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
NIPS 2020
Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs
ICML 2020
Counting and Sampling from Markov Equivalent DAGs Using Clique Trees
AAAI 2019
Budgeted Experiment Design for Causal Structure Learning
ICML 2018
Multi-domain Causal Structure Learning in Linear Systems
NIPS 2018
Learning Causal Structures Using Regression Invariance
NIPS 2017