AI RESEARCH
A lift for input-convex neural network training
arXiv CS.LG
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ArXi:2605.24274v1 Announce Type: new Input-convex neural networks (ICNNs) are widely used for log-concave density estimation, convex-potential normalizing flows, optimal transport, and transport-map inversion for high-dimensional Bayesian posteriors. These tasks share a structural constraint: the inter-layer weights of the ICNN must remain non-negative.