Introduces SFConvCNPs and SFVConvCNPs using set Fourier convolutions and Volterra expansions for translation-equivariant neural processes on irregular data with global receptive fields and linear scaling.
Convolutional conditional neural processes
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
NSP model fuses satellite and gauge data with neural processes and SDEs, outperforming 13 baselines and JAXA's operational product on a new 43k-sample US benchmark across six metrics.
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Revisiting Neural Processes via Fourier Transform and Volterra Series
Introduces SFConvCNPs and SFVConvCNPs using set Fourier convolutions and Volterra expansions for translation-equivariant neural processes on irregular data with global receptive fields and linear scaling.
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Neural Stochastic Processes for Satellite Precipitation Refinement
NSP model fuses satellite and gauge data with neural processes and SDEs, outperforming 13 baselines and JAXA's operational product on a new 43k-sample US benchmark across six metrics.