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surveillance) sensors can also be seen as temporal events. While data from current sensors can be manually converted into events for fast processing, it is also possible to develop hybrid structures where some
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-traditional, e.g., event data) and network structures (for sensor networks). In this project, we will investigate Bayesian deep learning approaches to training models under uncertainty for several sensing
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