Results 141 to 150 of about 173,664,564 (290)
On the Complexity of Tensor Formulae
, 2007 We consider formulae on base of sum, product, and tensor product of matrices . In particular, we consider matrices over the Boolean semi-ring B = (f0; 1g; _; ^) and over the two-element eld F 2 = (f0; 1g; +; ).
Carsten Damm, Carsten Da Mm
core
Advanced Intelligent Discovery, EarlyView.This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury +4 more
wiley +1 more source
On the Complexity of Tensor Formulae
, 1999 We consider formulae on base of sum, product, and tensor product of matrices . In particular, we consider matrices over the Boolean semi-ring B = (f0; 1g; _; ^) and over the two-element eld F 2 = (f0; 1g; +; ).
Carsten Damm +3 more
core
Advanced Intelligent Discovery, EarlyView.The behaviors of semiflexible polymers such as DNA and protein are often reshaped by coupled interactions. Monte Carlo simulations assist in studying these systems. This work recasts the traditional chain‐growth strategy into a new framework: a fixed number of chains grow synchronously, while less relevant chains to the target system are removed and ...
Yihan Zhao, Jizeng Wang
wiley +1 more source
Entropic and Geometric Population-Coherence Complementarity in Finite-Dimensional Quantum States. [PDF]
Entropy (Basel)Gil JJ.
europepmc +1 more source
Advanced Intelligent Discovery, EarlyView.Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi +2 more
wiley +1 more source
On flat tensor product surfaces
In this article, surfaces are studied that arise from taking the tensor product of two curves. More specific, classification theorems are presented of flat tensor product surfaces of two semi-Euclidean planar curves.
Goemans, Wendy, Van de Woestyne, Ignace
core
A note on linear preservers of certain ranks of tensor products of matrices
, 2015 In this note, we give a simple proof as well as an extension of a very recent result of B. Zheng, J. Xu and A. Fosner concerning linear maps between vector spaces of complex square matrices that preserve the rank of tensor products of matrices by using a
Lim, Ming Huat
core
A Quantum-Inspired Residual Self-Attention Network for Multimodal Sentiment Analysis. [PDF]
Entropy (Basel)Liu Y, Feng X, Zhong Y.
europepmc +1 more source
Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
Advanced Intelligent Systems, EarlyView.This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source