← Authors

Joao Marques-Silva

28 papers · 2013–2025 · 4 conferences · across top CS/AI conferences

Achievements

πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (24) 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (4) πŸƒ Academic Marathon (12) 🧭 Keyword Pioneer 🌈 Renaissance Researcher (6) 🐝 Cross-Pollinator (15) πŸ”¬ Deep Specialist (13) 🀝 Dynamic Duo (18) πŸ† Keyword Champion (4) πŸ”₯ Unstoppable (9) πŸ—ƒοΈ Keyword Collector (84) πŸ’Ž Century Club (28) πŸš€ Conference Pioneer

Conferences

IJCAI (15) AAAI (10) NIPS (2) ICML (1)

Top co-authors

Alexey Ignatiev (18) Nina Narodytska (8) Yacine Izza (7) Peter J. Stuckey (6) Xuanxiang Huang (4) Antonio Morgado (4) Alessandro Previti (3) MikolΓ‘Ε‘ Janota (3) Carlos MencΓ­a (2) Thomas Gerspacher (2)

Keywords

explainable ai (7) formal explanation (5) explainable artificial intelligence (5) decision tree (4) model explanation (4) model interpretability (3) black-box model (3) polynomial time (3) feature attribution (3) model-based diagnosis (3) model-agnostic explanation (2) interpretable machine learning (2) post-hoc explanation (2) sat solver (2) tree ensemble (2) abductive reasoning (2) formal methods (2) abductive explanation (2) algorithm design (1) branch and bound (1)

Papers

Towards Trustable SHAP Scores AAAI 2025
Most General Explanations of Tree Ensembles IJCAI 2025
Efficient and Rigorous Model-Agnostic Explanations IJCAI 2025
Updates on the Complexity of SHAP Scores IJCAI 2024
Delivering Inflated Explanations AAAI 2024
Solving Explainability Queries with Quantification: The Case of Feature Relevancy AAAI 2023
Eliminating the Impossible, Whatever Remains Must Be True: On Extracting and Applying Background Knowledge in the Context of Formal Explanations AAAI 2023
On Tackling Explanation Redundancy in Decision Trees (Extended Abstract) IJCAI 2023
Tractable Explanations for d-DNNF Classifiers AAAI 2022
Using MaxSAT for Efficient Explanations of Tree Ensembles AAAI 2022
Constraint-Driven Explanations for Black-Box ML Models AAAI 2022
Delivering Trustworthy AI through Formal XAI AAAI 2022
Reasoning-Based Learning of Interpretable ML Models IJCAI 2021
A Scalable Two Stage Approach to Computing Optimal Decision Sets AAAI 2021
Explanations for Monotonic Classifiers. ICML 2021
On Explaining Random Forests with SAT IJCAI 2021
Reasoning About Inconsistent Formulas IJCAI 2020
Explaining Naive Bayes and Other Linear Classifiers with Polynomial Time and Delay NIPS 2020
On Relating Explanations and Adversarial Examples NIPS 2019
Abduction-Based Explanations for Machine Learning Models AAAI 2019
Model-Based Diagnosis with Multiple Observations IJCAI 2019
Learning Optimal Decision Trees with SAT IJCAI 2018
Cardinality Encodings for Graph Optimization Problems IJCAI 2017
Prime Compilation of Non-Clausal Formulae IJCAI 2015
Literal-Based MCS Extraction IJCAI 2015
Efficient Model Based Diagnosis with Maximum Satisfiability IJCAI 2015
Solving QBF by Clause Selection IJCAI 2015
On Computing Minimal Correction Subsets IJCAI 2013