Interpretable LSTMs For Whole-Brain Neuroimaging Analyses

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Unmasking Clever Hans predictors and assessing what machines really learn (2019, methodology): “It has been extensively applied and validated on numerous applications 23,26,34,48 – 50 .”
When deep learning met code search (2019, background): “Fully explaining the performance differential in neural systems is an open research question [25, 33, 38].”
Toward Interpretable Machine Learning: Transparent Deep Neural Networks and Beyond (2020, unknown): “[127], [20], [55], [145], [36], [123], [112]) ultimately contributing to further our sci-”