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cs.LG2026
Provably Explaining Neural Additive Models
Shahaf Bassan, Yizhak Yisrael Elboher, Tobias Ladner +4
Despite significant progress in post-hoc explanation methods for neural networks, many remain heuristic and lack provable guarantees. A key approach for obtaining explanations with…
cs.LG2020
dtControl: Decision Tree Learning Algorithms for Controller Representation
Pranav Ashok, Mathias Jackermeier, Pushpak Jagtap +3
Decision tree learning is a popular classification technique most commonly used in machine learning applications. Recent work has shown that decision trees can be used to represent…