Probabilistic Programming is a way of defining probabilistic models by overloading the operations in standard programming language to have probabilistic meanings. The goal is to specify probabilistic ...

Accurate prediction of plant gene expression is essential for elucidating the regulatory mechanisms underlying plant development and stress adaptation. Traditional experimental approaches such as ...

Revised: This Reviewed Preprint has been revised by the authors in response to the previous round of peer review; the eLife assessment and the public reviews have been updated where necessary by the ...

1 Jiangxi Provincial Transportation Investment Maintenance Technology Group Co., Ltd., Nanchang, Jiangxi, China 2 Powerchina Jiangxi Electric Power Engineering Co., Ltd., Nanchang, Jiangxi, China ...

Abstract: The Graph Laplacian Mixture Model (GLMM) allows to infer multiple underlying graph structures from multivariate time series data. Given its effectiveness in identifying brain states from ...

Large language models are built on transformer architectures and power applications like chat, code generation, and search, but their growing scale with billions of parameters makes efficient ...

Artificial intelligence (AI) research has increasingly focused on enhancing the efficiency & scalability of deep learning models. These models have revolutionized natural language processing, computer ...

The Tesla Model Y has been the most popular electric car for a few years now, and it makes sense. The Model Y is reasonably priced for an EV while offering a good range and an excellent software ...

Abstract: Aiming at the problems of oriented-bounding-box-based (OBB-based) synthetic aperture radar (SAR) ship detection, which include the large model volume, the imbalance of positive and negative ...