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cs.LG2025
Out-of-Distribution Detection via Channelwise Feature Aggregation in Neural Network-Based Receivers
Marko Tuononen, Heikki Penttinen, Duy Vu +3
Neural network-based radio receivers are expected to play a key role in future wireless systems, making reliable Out-Of-Distribution (OOD) detection essential. We propose a post-ho…
cs.LG2024
Interpreting Deep Neural Network-Based Receiver Under Varying Signal-To-Noise Ratios
Marko Tuononen, Dani Korpi, Ville Hautamäki
We propose a novel method for interpreting neural networks, focusing on convolutional neural network-based receiver model. The method identifies which unit or units of the model co…