Imperial College London


Faculty of EngineeringDepartment of Computing

Research Postgraduate



patrick.henriksen18 Website




CDT space, room 402Sherfield BuildingSouth Kensington Campus





Publication Type

4 results found

Henriksen P, Leofante F, Lomuscio A, 2021, Repairing misclassifications in neural networks using limited data, SAC '22

Conference paper

Henriksen P, Hammernik K, Rueckert D, Lomuscio Aet al., 2021, Bias Field Robustness Verification of Large Neural Image Classifiers, British Machine Vision Conference (BMVC21)

Conference paper

Henriksen P, Lomuscio A, 2021, DEEPSPLIT: An Efficient Splitting Method for Neural Network Verification via Indirect Effect Analysis, Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}, Publisher: International Joint Conferences on Artificial Intelligence Organization

<jats:p>We propose a novel, complete algorithm for the verification and analysis of feed-forward, ReLU-based neural networks. The algorithm, based on symbolic interval propagation, introduces a new method for determining split-nodes which evaluates the indirect effect that splitting has on the relaxations of successor nodes. We combine this with a new efficient linear-programming encoding of the splitting constraints to further improve the algorithm’s performance. The resulting implementation, DeepSplit, achieved speedups of 1–2 orders of magnitude and 21-34% fewer timeouts when compared to the current SoA toolkits.</jats:p>

Conference paper

Henriksen P, Lomuscio A, 2020, Efficient Neural Network Verification via Adaptive Refinement and Adversarial Search, European Conference on Artificial Intelligence (ECAI20)

Conference paper

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