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Results for Interpretability

Publications & Outputs

  1. Towards explainable deep neural networks (xDNN)

    Angelov, P. & Soares, E., 1/10/2020, In: Neural Networks. 130, p. 185-194 10 p.

    Research output: Contribution to journalJournal articlepeer-review

  2. A survey of safety and trustworthiness of deep neural networks: Verification, testing, adversarial attack and defence, and interpretability

    Huang, X., Kroening, D., Ruan, W., Sharp, J., Sun, Y., Thamo, E., Wu, M. & Yi, X., 1/08/2020, In: Computer Science Review. 37, 35 p., 100270.

    Research output: Contribution to journalJournal articlepeer-review