Results 91 to 100 of about 6,652,811 (287)
A Graph-Learning Approach for Detecting Moral Conflict in Movie Scripts
Moral conflict is central to appealing narratives, but no methodology exists for computationally extracting moral conflict from narratives at scale. In this article, we present an approach combining tools from social network analysis and natural language
Frederic René Hopp +2 more
doaj +1 more source
In this study, the preparation techniques for silver‐based gas diffusion electrodes used for the electrochemical reduction of carbon dioxide (eCO2R) are systematically reviewed and compared with respect to their scalability. In addition, physics‐based and data‐driven modeling approaches are discussed, and a perspective is given on how modeling can aid ...
Simon Emken +6 more
wiley +1 more source
Discriminant Analysis with Graph Learning for Hyperspectral Image Classification
Linear Discriminant Analysis (LDA) is a widely-used technique for dimensionality reduction, and has been applied in many practical applications, such as hyperspectral image classification.
Mulin Chen, Qi Wang, Xuelong Li
doaj +1 more source
Human learning of hierarchical graphs
Humans are constantly exposed to sequences of events in the environment. Those sequences frequently evince statistical regularities, such as the probabilities with which one event transitions to another. Collectively, inter-event transition probabilities can be modeled as a graph or network.
Xiaohuan Xia +6 more
openaire +4 more sources
Fibrous benzenetrispeptide (BTP) hydrogels, fabricated via strain‐promoted azide‐alkyne cycloaddition (SPAAC) crosslinking, form robust, bioinert networks. These hydrogels can support 3D cell culture, where cell viability and colony growth depend on the fiber content.
Ceren C. Pihlamagi +5 more
wiley +1 more source
Predicting Atomic Charges in MOFs by Topological Charge Equilibration
An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi +2 more
wiley +1 more source
Learning Graph Quantization [PDF]
This contribution extends learning vector quantization to the domain of graphs. For this, we first identify graphs with points in some orbifold, then derive a generalized differentiable intrinsic metric, and finally extend the update rule of LVQ for generalized differentiable distance metrics.
Brijnesh J. Jain +3 more
openaire +1 more source
Artificial Intelligence as the Next Visionary in Liquid Crystal Research
The functions of AI in the research laboratory are becoming increasingly sophisticated, allowing the entire process of hypothesis formulation, material design, synthesis, experimental design, and reiterative testing to be automated. In our work, we conceive how the incorporation of AI in the laboratory environment will transform the role and ...
Mert O. Astam +2 more
wiley +1 more source
Molecular graph contrastive learning with line graph
Trapped by the label scarcity in molecular property prediction and drug design, graph contrastive learning (GCL) came forward. Leading contrastive learning works show two kinds of view generators, that is, random or learnable data corruption and domain knowledge incorporation.
Xueyuan Chen +6 more
openaire +2 more sources
Molecularly engineered memristors integrating Ag nanoparticle–embedded synthetic DNA with quasi‐2D halide perovskites enable ultra‐low‐operational voltage, forming‐free resistive switching, and record‐low power density. This synergistic integration of customized DNA and 2D OHP in bio‐hybrid architecture enhances charge transport, reduces variability ...
Kavya S. Keremane +9 more
wiley +1 more source

