Data assimilation (DA) is a mathematical family of methods that allows the combination of observations and models. The model is used to fill observational gaps, and ...

Geographical Gaussian Process Regression (GGPR): A Spatial Machine Learning Model Based on Spatial Similarity: defined as A-Xing Zhu et al. (2018): "The more similar geographic configurations of two ...

perception rests on an agent's model of how its sensory input comes about and the inferences it draws based on this model. These inferences are necessarily uncertain. Here, we illustrate how the ...

To address this challenge, we propose C3DGS that compresses 3D Gaussian model and ensures the quality of surface reconstruction of large-scale scenes in the face of heavy computational costs. Our ...

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and state-space models to enhance the uncertainty representation capability of deep networks. And, by incorporating planar flows (PFs), it relaxes the Gaussian assumption in traditional models, ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the random neighborhoods regression technique, where the goal is to predict a single numeric value. Compared ...

Global biodiversity is declining at an unprecedented rate, with agriculture as a major driver. There is mounting evidence that intercropping can increase insect biodiversity while maintaining or ...

OpenAI just released o3-mini, a reasoning model that’s faster, cheaper, and more accurate than its predecessor. On Thursday, Microsoft announced that it’s rolling OpenAI's reasoning model o1 ...

Tesla has revealed a new-look Model Y meant for the Chinese and other Asian-Pacific markets, marking the first major update to the SUV since its launch in 2020. The redesign comes as Tesla ...

Developing a linear TV app can be complex due to compatibility requirements and the need to deliver content in real-time. However, VPlayed’s hiring model simplifies this process, allowing you to ...