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Adnan Darwiche

32 papers · 2009–2024 · 8 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (15) 🌍 Conference Polyglot (8) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (14) πŸ—ΊοΈ Taxonomy Completionist (17) 🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🀝 Dynamic Duo (19) πŸ† Keyword Champion (2) πŸ”¬ Deep Specialist (10) πŸ—ƒοΈ Keyword Collector (50) πŸ”₯ Unstoppable (12) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ’Ž Century Club (32)

Conferences

IJCAI (9) NIPS (9) PGM (5) AAAI (3) ICML (3) AISTATS (1) CLEAR (1) UAI (1)

Top co-authors

Arthur Choi (19) Yujia Shen (6) Guy Van den Broeck (5) Yizuo Chen (4) Andy Shih (3) Eunice Yuh-Jie Chen (3) Haiying Huang (3) Khaled S Refaat (2) Chunxi Ji (1) Arthur Choi Choi (1)

Keywords

bayesian network (10) graphical model (9) probabilistic graphical model (8) probabilistic modeling (5) explainable ai (4) probabilistic model (4) arithmetic circuit (4) structure learning (3) sentential decision diagram (3) probabilistic sentential decision diagram (3) counterfactual reasoning (2) supervised learning (2) inference algorithm (2) structural causal model (2) exact inference (2) bayesian inference (2) map inference (2) parameter estimation (2) lifted inference (2) causal inference (2)

Papers

Identifying Causal Effects Under Functional Dependencies NIPS 2024
On the Complexity of Counterfactual Reasoning IJCAI 2023
An Algorithm and Complexity Results for Causal Unit Selection CLEAR 2023
On the definition and computation of causal treewidth UAI 2022
On Quantifying Literals in Boolean Logic and its Applications to Explainable AI (Extended Abstract) IJCAI 2022
On the Computation of Necessary and Sufficient Explanations AAAI 2022
On Recovering from Modeling Errors Using Testing Bayesian Networks ICML 2021
Supervised Learning with Background Knowledge PGM 2020
A New Perspective on Learning Context-Specific Independence PGM 2020
Conditional Independence in Testing Bayesian Networks ICML 2019
Compiling Bayesian Network Classifiers into Decision Graphs AAAI 2019
Structured Bayesian Networks: From Inference to Learning with Routes AAAI 2019
A Symbolic Approach to Explaining Bayesian Network Classifiers IJCAI 2018
Formal Verification of Bayesian Network Classifiers PGM 2018
On the Relative Expressiveness of Bayesian and Neural Networks PGM 2018
Open-World Probabilistic Databases: An Abridged Report IJCAI 2017
Tractability in Structured Probability Spaces NIPS 2017
Optimal Feature Selection for Decision Robustness in Bayesian Networks IJCAI 2017
On Relaxing Determinism in Arithmetic Circuits ICML 2017
On Pruning with the MDL Score PGM 2016
Tractable Operations for Arithmetic Circuits of Probabilistic Models NIPS 2016
Enumerating Equivalence Classes of Bayesian Networks using EC Graphs AISTATS 2016
Learning Bayesian networks with ancestral constraints NIPS 2016
A Top-Down Compiler for Sentential Decision Diagrams IJCAI 2015
Tractable Learning for Complex Probability Queries NIPS 2015
Tractable Learning for Structured Probability Spaces: A Case Study in Learning Preference Distributions IJCAI 2015
Data Compression for Learning MRF Parameters IJCAI 2015
Decomposing Parameter Estimation Problems NIPS 2014
EDML for Learning Parameters in Directed and Undirected Graphical Models NIPS 2013
An Exact Algorithm for Computing the Same-Decision Probability IJCAI 2013
On the Complexity and Approximation of Binary Evidence in Lifted Inference NIPS 2013
Approximating MAP by Compensating for Structural Relaxations NIPS 2009