Space Explanations of Neural Network Classification
Fuente:
arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866908679380402176 |
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| author | Labbaf, Faezeh Kolárik, Tomáš Blicha, Martin Fedyukovich, Grigory Wand, Michael Sharygina, Natasha |
| author_facet | Labbaf, Faezeh Kolárik, Tomáš Blicha, Martin Fedyukovich, Grigory Wand, Michael Sharygina, Natasha |
| contents | We present a novel logic-based concept called Space Explanations for classifying neural networks that gives provable guarantees of the behavior of the network in continuous areas of the input feature space. To automatically generate space explanations, we leverage a range of flexible Craig interpolation algorithms and unsatisfiable core generation. Based on real-life case studies, ranging from small to medium to large size, we demonstrate that the generated explanations are more meaningful than those computed by state-of-the-art. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_22498 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Space Explanations of Neural Network Classification Labbaf, Faezeh Kolárik, Tomáš Blicha, Martin Fedyukovich, Grigory Wand, Michael Sharygina, Natasha Machine Learning Logic in Computer Science We present a novel logic-based concept called Space Explanations for classifying neural networks that gives provable guarantees of the behavior of the network in continuous areas of the input feature space. To automatically generate space explanations, we leverage a range of flexible Craig interpolation algorithms and unsatisfiable core generation. Based on real-life case studies, ranging from small to medium to large size, we demonstrate that the generated explanations are more meaningful than those computed by state-of-the-art. |
| title | Space Explanations of Neural Network Classification |
| topic | Machine Learning Logic in Computer Science |
| url | https://arxiv.org/abs/2511.22498 |