An upsampled convolutional autoencoder reconstructs simulated scintillator pulse times with 0.19 ns MAE and amplitudes with 23.2 mV MAE, about four to five times more accurate than the baseline model.
Artificial Neural Networks on FPGAs for Real-Time Energy Reconstruction of the ATLAS LAr Calorimeters
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Development and Explainability of Models for Machine-Learning-Based Reconstruction of Signals in Particle Detectors
An upsampled convolutional autoencoder reconstructs simulated scintillator pulse times with 0.19 ns MAE and amplitudes with 23.2 mV MAE, about four to five times more accurate than the baseline model.