Results 201 to 210 of about 476,790 (313)

PathTIGR: A pathway topology-informed graph representation learning framework for immunotherapy response prediction. [PDF]

Sci Adv
Li X, He Y, Wu J, Wang Z, Zhao X, Zhang Y, Pan B, Tang Y, Han J.   +8 more
europepmc   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Spatially multimodal and multiscale network for representation learning from spatial multi-omics. [PDF]

BMC Genomics
Zhang F, Peng C.
europepmc   +1 more source

Visual target tracking via weighted non-sparse representation and online metric learning

, 2013
In this paper, we propose online metric learning tracking method that consider visual tracking as a similarity measurement problem, and incorporates adaptive metric learning and generative histogram model based on non-sparse linear representation into ...
Duan, Jingdi, Fan BJ(范保杰), Cong Y(丛杨)   +2 more
core  

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Self-supervised representation learning reveals explainable physiological structure in high-dimensional magnetocardiography. [PDF]

NPJ Digit Med
Kranz DD, Kahriman O, Dischl D, Treskatsch S, Sander A, Brachmann J, Park JW, Wessel N.   +7 more
europepmc   +1 more source

Prediction of Surface Topography Parameters in Direct Laser Interference Patterning of Stainless Steel Using Infrared Monitoring and Convolutional Neural Networks

Advanced Engineering Materials, EarlyView.
This study presents an infrared monitoring approach for direct laser interference patterning (DLIP) combined with a convolutional neural network (CNN). Thermal emission data captured during structuring are used to predict surface topography parameters.
Lukas Olawsky, Marcelo Sallese, Leander Kläber, Clemens Kuhn, Keming Du, Andrés Fabián Lasagni   +5 more
wiley   +1 more source

Multimodal representation and learning.

, 2019
Recent years have seen an explosion in multimodal data on the web. It is therefore important to perform multimodal learning to understand the web. However, it is challenging to join various modalities because each modality has a different representation and correlational structure.
openaire   +2 more sources

Joint representation learning for oncology applications. [PDF]

Bioinformatics
Nandan T, Fan B, Håkansson S, Jutzeler CR, Brüningk SC.   +4 more
europepmc   +1 more source

Zein‐Based Adhesives: Sustainable Extraction and Application in Bioadhesive Technologies

Advanced Engineering Materials, EarlyView.
Zein is extracted from corn gluten meal using a simple and scalable process with high yield (~90%). The resulting protein is applied in bioadhesives modified with Ca2+ and Fe3+ ions, exhibiting substrate‐dependent adhesion. The findings demonstrate competitive bonding performance and highlight the role of ionic interactions in tuning adhesion ...
Paula Bertolino Sanvezzo, Daniela Winsley Valereto Friozi, Vinícius de Oliveira, Marcia Cristina Branciforti   +3 more
wiley   +1 more source