Results 181 to 190 of about 680,508 (291)

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Machine learning and bifurcation analysis in a discrete predator-prey model with neem-induced mortality. [PDF]

Sci Rep
Mehmood T, Rafaqat M, Saleem S, Merga FE.   +3 more
europepmc   +1 more source

Significance of Discrete Mathematics in IT and Communication Field

, 2018
Sumaira Taj
openalex   +1 more source

Graph Attention Neural Networks for Interpretable and Generalizable Prediction of Janus III–Vi Van Der Waals Heterostructures

Advanced Intelligent Discovery, EarlyView.
A crystal graph neural network based on the attention mechanism is proposed in this work. The model dynamically weights features through the attention mechanism, enabling precise prediction of properties of material from structural features. Here, taking Janus III–VI van der Waals heterostructures as a representative case, the properties have been ...
Yudong Shi, Zhao Zheng, Yinggan Zhang, Zhou Cui, Peng Lin, Cuilian Wen, Baisheng Sa, Zhimei Sun   +7 more
wiley   +1 more source

Modelling the dynamically consistent numerical methods for COVID-19 disease with cost effectiveness strategies. [PDF]

Sci Rep
Li S, Abbas MA, Khan IU, Akgül A, Alkhathami AG, Hassani MK.   +5 more
europepmc   +1 more source

Random discrete groups of Möbius transformations : probabilities and limit set dimensions : a thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Mathematics at Massey University, Albany, New Zealand

, 2017
Graeme K O'Brien
openalex   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Finite-Time Dissipative Fault Estimate and Event-Triggered Fault-Tolerant Synchronization Control for Discrete Semi-Markov Jumping Neural Networks. [PDF]

Entropy (Basel)
Zhu X, Wang Y, Chen Y.
europepmc   +1 more source

A Mathematical Unification of the Helix–Light–Vortex (HLV) Framework: Discrete Geometry, Spiral Time, Unified Lagrangians, and An Effective Field Theory Approach to Geometric Unification

Marcel Krüger
openalex   +1 more source

Mathematical Discretization of Size-Exclusion Chromatograms Applied to Commercial Corn Maltodextrins [PDF]

, 2006
Valéry Normand, Fabrice Avaltroni, Pierre‐Etienne Bouquerand   +2 more
openalex   +1 more source