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cs.LG2025
Scalable Spatiotemporal Inference with Biased Scan Attention Transformer Neural Processes
Daniel Jenson, Jhonathan Navott, Piotr Grynfelder +4
Neural Processes (NPs) are a rapidly evolving class of models designed to directly model the posterior predictive distribution of stochastic processes. While early architectures we…
stat.AP2025
Real-time small area estimation of food security in Zimbabwe: integrating mobile-phone and face-to-face surveys using joint multilevel regression and poststratification
Sahoko Ishida, Adam Howes, Valerie Bradley +14
Real-time, fine-grained monitoring of food security is essential for enabling timely and targeted interventions, thereby supporting the global goal of achieving zero hunger - a key…
stat.ML2025
DeepRV: Accelerating Spatiotemporal Inference with Pre-trained Neural Priors
Jhonathan Navott, Daniel Jenson, Seth Flaxman +1
Gaussian Processes (GPs) provide a flexible and statistically principled foundation for modelling spatiotemporal phenomena, but their scaling makes them intractable for la…