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Exploring Internal Representations Learned by Autoencoders for Sleep EEG
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Strategies and Structures for Biological Datasets Integration and Knowledge Discovery
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Biological Discovery via Data Science: Multigranular Artificial Intelligence Approaches for Cells, Cerebra and Cruise Ships
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Modern Computer Science Approaches in Biology: From Predicting Molecular Functions to Modeling Protein Structure
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Understanding Internal Feature Development in Deep Convolutional Neural Networks for Time Series
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Towards Instantaneous Mental Health Screening From Voice Using Machine and Deep Learning
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Attention-based Deep Learning Models for Text Classification and their Interpretability
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Boosting Gene Expression Clustering with System-Wide Biological Information and Deep Learning
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Contributions to Collective Dynamical Clustering-Modeling of Discrete Time Series
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Spatial and Temporal Learning in Robotic Pick-and-Place Domains via Demonstrations and Observations
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