Abstract: Accurate tracking of targets is vital for safe and reliable operations, particularly in complex and dynamic environments such as urban areas. Traditional tracking methods, including Kalman ...

Recursive language models (RLMs) are an inference technique developed by researchers at MIT CSAIL that treat long prompts as an external environment to the model. Instead of forcing the entire prompt ...

SVGP-KAN is a library for building interpretable, probabilistic, and scalable neural networks. It merges the architecture of Kolmogorov-Arnold Networks (KANs) with ...

Ever wonder why ChatGPT slows down during long conversations? The culprit is a fundamental mathematical challenge: Processing long sequences of text requires massive computational resources, even with ...

3D Gaussian Splatting (3DGS) has shown impressive results in real-time novel view synthesis. However, it often struggles under sparse-view settings, producing undesirable artifacts such as floaters, ...

ABSTRACT: This paper introduces a method to develop a common model based on machine learning (ML) that predicts the mechanical behavior of a family with three composite materials. The latter are ...

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Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...