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We present methods for detecting cell events in simulated node pore sensing signals. First, we propose an inverse formulation for detection and methods for solving it. Using our complex simulation model, we also show that a data-driven deep learning approach is able to effectively learn to identify cell events and apply them on unseen examples, even with noise and model mismatch.

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