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Appendices: Score-based Source Separation with Applications to Digital Communication Signals

Neural Information Processing Systems

During source separation, this presumably results in a noisier estimate of the SOI in comparison to mixtures with no additional background noise. We estimated the SNR to be 16.9dB by averaging across multiple samples. The dotted black curve on the left of Figure G.2 is a presumable lower bound on the BER by accounting for the magnitude of the background noise and modeling it as additive white Gaussian noise.





LocalSignalAdaptivity: ProvableFeatureLearning inNeuralNetworksBeyondKernels

Neural Information Processing Systems

Specifically,we prove that, forasimple data distribution with sparsesignal amidst high-variance noise, a simple convolutional neural network trained using stochastic gradient descent simultaneously learnstothreshold outthenoiseandfindthesignal.