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Correcting gradient-based interpretations of deep neural networks for genomics
Post hoc attribution methods can provide insights into the learned patterns from deep neural networks (DNNs) trained on high-throughput functional genomics data. However, in practice, their resultant attribution maps can be challenging to interpret due to spurious importance scores for seemingly arb...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10169356/ https://www.ncbi.nlm.nih.gov/pubmed/37161475 http://dx.doi.org/10.1186/s13059-023-02956-3 |