GraphGP delivers a linear-scaling GPU implementation of Vecchia's sparse precision approximation for Gaussian processes on arbitrary point sets using a bit-reversed k-d tree and CUDA kernels.
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Develops an NNGP spatio-temporal model with SMC squared inference for haplotype frequency estimation from pooled genetic data, demonstrated on 3- and 6-marker antimalarial resistance datasets in Africa.
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GraphGP: Scalable Gaussian Processes with Vecchia's Approximation
GraphGP delivers a linear-scaling GPU implementation of Vecchia's sparse precision approximation for Gaussian processes on arbitrary point sets using a bit-reversed k-d tree and CUDA kernels.