arXiv:2602.21334v1 Announce Type: new Abstract: As satellites have proliferated, interest has increased in autonomous rendezvous, proximity operations, and docking (ARPOD). A fundamental challenge in these tasks is the uncertainties when operating in space, e.g., in measurements of satellites’ states, which can make future states difficult to predict. Another challenge is that satellites’ onboard processors are typically much slower than their terrestrial counterparts. Therefore, to address these challenges we propose to solve an ARPOD problem with feedback optimization, which […]

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arXiv:2602.20651v1 Announce Type: cross Abstract: In modern applications such as ECG monitoring, neuroimaging, wearable sensing, and industrial equipment diagnostics, complex and continuously structured data are ubiquitous, presenting both challenges and opportunities for functional data analysis. However, existing methods face a critical trade-off: conventional functional models are limited by linearity, whereas deep learning approaches lack interpretable region selection for sparse effects. To bridge these gaps, we propose a sparse Bayesian functional deep neural network (sBayFDNN). It learns adaptive functional […]

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Introduction If you are reading this blog, you might have been familiar with what Git is and how it has been an integral part of software development. Similarly, Data Version Control (DVC) is an open-source, Git-based version management for Machine Learning development that instills best practices across the teams. A system called data version control manages and tracks changes to data and machine learning models in a collaborative and reproducible manner. It draws inspiration from version control systems […]

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With the increasing cost of labor, smart agriculture has emerged as a key trend for the future of agricultural development. This paper presents an integrated approach for tomato maturity clas-sification and yield estimation using both RGB and multispectral images. The proposed approach consists of three main components: tomato detection, tomato tracking and counting, and maturity classification of tomatoes. YOLOv8 combined with OSNet is first employed to detect tomatoes, while StrongSORT is then adopted to track consistent identities across […]

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arXiv:2406.19958v2 Announce Type: replace Abstract: Bayesian Additive Regression Trees (BART) is a popular Bayesian non-parametric regression model that is commonly used in causal inference and beyond. Its strong predictive performance is supported by well-developed estimation theory, comprising guarantees that its posterior distribution concentrates around the true regression function at optimal rates under various data generative settings and for appropriate prior choices. However, the computational properties of the widely-used BART sampler proposed by Chipman et al. (2010) are yet […]

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:::info Astounding Stories of Super-Science July, 2008, by Astounding Stories is part of HackerNoon’s Book Blog Post series. You can jump to any chapter in this book here. The Call of the Wild – The Sounding of the Call Astounding Stories of Super-Science July 2008: The Call of the Wild – The Sounding of the Call By Jack London ::: When Buck earned sixteen hundred dollars in five minutes for John Thornton, he made it possible for his master […]

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