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cs.LG2025
Floating-Point Neural Networks Are Provably Robust Universal Approximators
Geonho Hwang, Wonyeol Lee, Yeachan Park +2
The classical universal approximation (UA) theorem for neural networks establishes mild conditions under which a feedforward neural network can approximate a continuous function $f…
cs.LG2024★ 28 cited
Scalable Spatiotemporal Prediction with Bayesian Neural Fields
Feras Saad, Jacob Burnim, Colin Carroll +4
Spatiotemporal datasets, which consist of spatially-referenced time series, are ubiquitous in diverse applications, such as air pollution monitoring, disease tracking, and cloud-de…