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Mostrati risultati da 1 a 8 di 8
Three Perspectives on Anomaly Detection in Deep Learning
2023 Craighero, F
LACE 2.0: an interactive R tool for the inference and visualization of longitudinal cancer evolution
2023 Ascolani, G; Angaroni, F; Maspero, D; Craighero, F; Bhavesh, N; Piazza, R; Damiani, C; Ramazzotti, D; Antoniotti, M; Graudenzi, A
Unity is strength: Improving the detection of adversarial examples with ensemble approaches
2023 Craighero, F; Angaroni, F; Stella, F; Damiani, C; Antoniotti, M; Graudenzi, A
A review of computational strategies for denoising and imputation of single-cell transcriptomic data
2021 Patruno, L; Maspero, D; Craighero, F; Angaroni, F; Antoniotti, M; Graudenzi, A
On the use of topological features of metabolic networks for the classification of cancer samples
2021 Machicao, J; Craighero, F; Maspero, D; Angaroni, F; Damiani, C; Graudenzi, A; Antoniotti, M; Bruno, O
Combining multi-target regression deep neural networks and kinetic modeling to predict relative fluxes in reaction systems
2021 Patruno, L; Craighero, F; Maspero, D; Graudenzi, A; Damiani, C
Investigating the Compositional Structure Of Deep Neural Networks
2020 Craigher, F; Angaroni, F; Graudenzi, A; Stella, F; Antoniotti, M
Understanding deep learning with activation pattern diagrams
2020 Craighero, F; Angaroni, F; Graudenzi, A; Stella, F; Antoniotti, M
Mostrati risultati da 1 a 8 di 8
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