Covariance neural networks offer principled substitute for known structure in relational inductive biases; VNNs connect to PCA and improve stability with finite-sample estimation errors
Read the original at arxiv.org→arXiv:2611.07212v1 Announce Type: new Abstract: Relational inductive biases such as grids or graphs allow neural networks with fewer trainable parameters and improved generalization, but require a known structure...
Original headline: "Canonical Correlation Neural Networks"
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- Nov 6, 05:00 UTC arXiv cs.LG lead source Canonical Correlation Neural Networks