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20242026
most citedSolving Probabilistic Verification Problems of Neural Networks using Branch and Bound

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cs.AI2026

Computing Actual Causes for Neural Network Predictions under Structured Causal Inputs

Jannick Strobel, Muqsit Azeem, Stefan Leue

Explaining the predictions of neural networks is a central challenge in trustworthy AI. Existing explanation methods, such as those based on feature attribution or minimal sufficie…

cs.LG2026

Verified SHAP: Provable Bounds for Exact Shapley Values of Neural Networks

David Boetius, Shahaf Bassan, Guy Katz +2

Shapley additive explanations (SHAP) are widely recognised as computationally intractable for neural networks, since they induce an exponential search space over the input features…