Abstract: Time series prediction techniques have been used in many real-world applications such as financial market prediction, electric utility load forecasting , weather and environmental state ...

Microsoft Research conducts fundamental science and technology research across a spectrum of research areas. With labs around the globe we pursue breakthroughs across the computing and AI stack to ...

RFF can be applicable to many other machine learning algorithms than the above. The author will provide implementations of the other algorithms soon. This module supports training/inference on GPU.

In this rapidly growing digital age, the way we represent and process information has become increasingly sophisticated, with vector data standing at the forefront of this evolution. Vector data, ...

Nearly a quarter of bipolar disorder (BD) patients were misdiagnosed as major depressive disorder (MDD) patients, which cannot be corrected until mania/hypomania develops. It is important to recognize ...

Abstract: The unprecedented non-contact, non-invasive, and privacy-preserving nature of radar sensors has enabled various healthcare applications, including vital sign monitoring, fall detection, gait ...

Danny Antaki, William M Brandler, Jonathan Sebat; SV 2: Accurate Structural Variation Genotyping and De Novo Mutation Detection from Whole Genomes, Bioinformatics ...

Considering the strong non-linear time-varying behavior of dam deformation, a novel prediction model, called Levy flight-based grey wolf optimizer optimized support vector regression (LGWO-SVR), is ...

Machine learning is a branch of artificial intelligence that includes methods, or algorithms, for automatically creating models from data. Unlike a system that performs a task by following explicit ...

This is a carefully curated compendium of articles & tutorials covering all things AI, Data Science & Machine Learning for the beginner to advanced practitioner. I will be periodically updating this ...

$${U}_{\Phi ({\boldsymbol{x}})}={\rm{\exp }}(i\sum _{S\subseteq [n]}{\varphi }_{S}({\boldsymbol{x}})\prod _{i\in S}{Z}_{i})$$ The two classifiers—a variational ...

Dimensionality reduction is important for the high-dimensional nature of data in the process industry, which has made latent variable modeling methods popular in recent years. By projecting ...