Results 201 to 210 of about 3,906,906 (309)
Designing Memristive Materials for Artificial Dynamic Intelligence
Key characteristics required of memristors for realizing next‐generation computing, along with modeling approaches employed to analyze their underlying mechanisms. These modeling techniques span from the atomic scale to the array scale and cover temporal scales ranging from picoseconds to microseconds. Hardware architectures inspired by neural networks
Youngmin Kim, Ho Won Jang
wiley +1 more source
Corrigendum: Magnetic sense-dependent probabilistic decision-making in humans. [PDF]
Oh IT, Kim SC, Kim Y, Kim YH, Chae KS.
europepmc +1 more source
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
A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali+5 more
wiley +1 more source
Unveiling a novel S-Box strategy: The dynamic 3D scrambling approach. [PDF]
Ahmad Khan N+7 more
europepmc +1 more source
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+12 more
wiley +1 more source
MATHEMATICAL ANALYSIS OF A FEW MIGRATORY FLOW MODELS WITH ENDOGENEOUS MIGRATION PROBABILITY
Manuel Philippe Émile Garçon
openalex +1 more source