<ul data-eligibleForWebStory="false"><li>Researchers have developed a new algorithm for solving probabilistic verification problems of neural networks.</li><li>The algorithm is based on computing and refining lower and upper bounds on probabilities over the outputs of a neural network.</li><li>By utilizing advanced bound propagation and branch and bound techniques, the algorithm outperforms existing probabilistic verification methods, reducing solution times significantly.</li><li>Empirical evaluations and theoretical analysis demonstrate the soundness and efficiency of the algorithm in various scenarios, even outperforming dedicated algorithms for specific probabilistic verification problems.</li></ul>

Solving Probabilistic Verification Problems of Neural Networks using Branch and Bound

Discover more