To address these gaps, two-dimensional (2D) Kernel Density Estimation (KDE) plots have been introduced as a novel tool for visualising the interplay between external demands and internal responses in ...

Machine learning transforms the landscape of 2D materials design, particularly in accelerating discovery, optimization, and screening processes. This review has delved into the historical and ongoing ...

Armed with KTNN, we propose a tensor robust kernel PCA (TRKPCA) model for handling multidimensional data, which decomposes the observed tensor into an implicit low-rank component and a sparse ...

This paper shows that adaptive kernel density estimator (KDE) can be derived effectively from Isolation Kernel. Existing adaptive KDEs often employ a data independent kernel such as Gaussian kernel.

Evolving its EcoStruxure Data Center Solutions portfolio, Schneider Electric introduced a Prefabricated Modular EcoStruxure Pod Data Center solution that consolidates infrastructure for liquid cooling ...

Here, molecular graphs derived from the one-electron density matrix are introduced within a more general effort to explore whether incorporating electronic structure awareness allows a single model to ...

As AI drives data center density to new extremes, Shumate Engineering unveils a game-changing hybrid cooling design. In this episode of the DCF Show podcast, Daren Shumate and Steve Spinazzola explain ...

Non-Rigid Structure from Motion - Matlab software for reconstructing non-rigid 3D shape from tracking data. (by Lorenzo Torresani, Aaron Hertzmann, and Chris Bregler / Movement Group) OpenVIDIA : ...

Data for ab initio Density Matrix Renormalization Group (DMRG) with Spin-Orbit Coupling (SOC) This includes the input and output files for the following paper: Huanchen Zhai, and Garnet Kin-Lic Chan. ...