Results 171 to 180 of about 259,269 (327)
Contextual embeddings, derived from deep language models (DLMs), provide a continuous vectorial representation of language. This embedding space differs fundamentally from the symbolic representations posited by traditional psycholinguistics.
Ariel Goldstein +21 more
doaj +1 more source
Integrating topic modeling and word embedding to characterize violent deaths. [PDF]
Arseniev-Koehler A +4 more
europepmc +1 more source
This work introduces a novel approach for encoding and storing information in the liquid state in microdroplet arrays. These liquid‐in‐liquid prints are generated by a droplet printing system capable of dynamically setting the composition of each droplet pixel.
Maximilian Breitfeld +5 more
wiley +1 more source
Measuring novelty in science with word embedding. [PDF]
Shibayama S, Yin D, Matsumoto K.
europepmc +1 more source
Malware Classification using API Call Information and Word Embeddings
Sahil Aggarwal
openalex +2 more sources
Role of the Recombination Zone in Organic Light‐Emitting Devices
This review summarizes the critical role of the recombination zone in organic light‐emitting diodes (OLEDs). We highlight that broadening the recombination zone in OLEDs based on emissive layers with balanced charge transport and high photoluminescence quantum yields provides a promising route toward achieving both long operational lifetime and high ...
Yungui Li, Karl Leo
wiley +1 more source
Deep Neural Network Framework Based on Word Embedding for Protein Glutarylation Sites Prediction. [PDF]
Liu CM +4 more
europepmc +1 more source
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam +6 more
wiley +1 more source
Word Embedding Distribution Propagation Graph Network for Few-Shot Learning. [PDF]
Zhu C, Wang L, Han C.
europepmc +1 more source

