Results 151 to 160 of about 272,443 (187)

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

A Machine Learning Perspective on the Brønsted–Evans–Polanyi Relation in Water‐Gas Shift Catalysis on MXenes

Advanced Intelligent Discovery, EarlyView.
Machine learning predicts activation energies for key steps in the water‐gas shift reaction on 92 MXenes. Random Forest is identified as the most accurate model. Reaction energy and reactant LogP emerge as key descriptors. The approach provides a predictive framework for catalyst design, grounded in density functional theory data and validated through ...
Kais Iben Nassar, Tiago L. P. Galvão, José D. Gouveia, José R. B. Gomes   +3 more
wiley   +1 more source

On a coupled fixed point problem in topological vector spaces

, 2012
Zoran D‎. Mitrović
openalex   +1 more source

Widened Attention‐Enhanced Atrous Convolutional Network for Efficient Embedded Vision Applications under Resource Constraints

Advanced Intelligent Systems, EarlyView.
The article introduces WACEfNet, a new convolutional neural network architecture optimized for efficient aerial image analysis under resource constraints. It creatively integrates attention mechanisms and atrous convolutions into a compact widened residual network framework.
Md Meftahul Ferdaus, Mahdi Abdelguerfi, Kendall N. Niles, Ken Pathak, Joe Tom   +4 more
wiley   +1 more source

Two Fixed Point Theorems in Topological vector space Valued Cone Metric Spaces with Complete Topological Algebra Cones

, 2012
Tadesse Bekeshie
openalex   +1 more source

Joint Situational Assessment‐Hierarchical Decision‐Making Framework for Maneuver Intent Decisions

Advanced Intelligent Systems, EarlyView.
This study introduces a new framework for decision‐making in unmanned combat aerial vehicles (UCAVs), integrating graph convolutional networks and hierarchical reinforcement learning (HRL). The method tackles adopts a curriculum‐based training approach guided by cross‐entropy rewards.
Ruihai Chen, Hao Li, Guanwei Yan, Haojie Peng, Qian Zhang   +4 more
wiley   +1 more source

Weak convergence of probability measures: a topological vector space point of view

, 2013
Liang Hong
openalex   +2 more sources

Applied Artificial Intelligence in Materials Science and Material Design

Advanced Intelligent Systems, EarlyView.
AI‐driven methods are transforming materials science by accelerating material discovery, design, and analysis, leveraging large datasets to enhance predictive modeling and streamline experimental techniques. This review highlights advancements in AI applications across spectroscopy, microscopy, and molecular design, enabling efficient material ...
Emigdio Chávez‐Angel, Martin Børstad Eriksen, Alejandro Castro‐Alvarez, Jose H. Garcia, Marc Botifoll, Oscar Avalos‐Ovando, Jordi Arbiol, Aitor Mugarza   +7 more
wiley   +1 more source

Weak Integrals and Bounded Operators in Topological Vector Spaces

, 2013
Lakhdar Meziani, Saud M. Alsulami
openalex   +2 more sources

Reprogrammable, In‐Materia Matrix‐Vector Multiplication with Floppy Modes

Advanced Intelligent Systems, EarlyView.
This article describes a metamaterial that mechanically computes matrix‐vector multiplications, one of the fundamental operations in artificial intelligence models. The matrix multiplication is encoded in floppy modes, near‐zero force deformations of soft matter systems.
Theophile Louvet, Parisa Omidvar, Marc Serra‐Garcia   +2 more
wiley   +1 more source