Quadratic Neuron-empowered Heterogeneous Autoencoder for Unsupervised Anomaly Detection

arXiv:2204.01707v2 Announce Type: replace-cross
Abstract: Inspired by the complexity and diversity of biological neurons, a quadratic neuron is proposed to replace the inner product in the current neuron with a simplified quadratic function. Employing such a novel type of neurons offers a new perspective on developing deep learning. When analyzing quadratic neurons, we find that there exists a function such that a heterogeneous network can approximate it well with a polynomial number of neurons but a purely conventional or quadratic …

abstract anomaly anomaly detection arxiv autoencoder complexity cs.lg cs.ne current deep learning detection diversity function neuron neurons novel perspective product simplified type unsupervised