Neural Processes
PulseAugur coverage of Neural Processes — every cluster mentioning Neural Processes across labs, papers, and developer communities, ranked by signal.
3 day(s) with sentiment data
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New APIC method calibrates physics models using Neural Processes
Researchers have developed APIC, a new method for calibrating physics models that suffer from discrepancies with real-world data. This approach extends the Kennedy-O'Hagan framework by using Neural Processes to enable s…
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New neural process methods leverage Fourier and Volterra series
Researchers have developed new methods to improve neural processes (NPs), a type of probabilistic model used for function approximation from limited data. Their work addresses limitations in existing translation-equivar…
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Research paper details three costs of amortizing Gaussian Process inference
A new research paper details three primary costs associated with amortizing Gaussian Process inference using Neural Processes. The study identifies label contamination, an information bottleneck, and amortization error …
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New BSA-TNP model offers scalable, accurate spatiotemporal inference
Researchers have introduced a new neural process model called the Biased Scan Attention Transformer Neural Process (BSA-TNP). This architecture aims to improve scalability and accuracy for modeling complex spatiotempora…