Results 141 to 150 of about 96,400 (324)
Sentiment analysis with covariate-assisted word embeddings [PDF]
, 2021 Shirong Xu, Ben Dai, Junhui Wang
openalex +1 more source
Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application
Advanced Materials, EarlyView.This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong +12 more
wiley +1 more source
On the Varieties of Fractal Geometry of Word Embeddings
Proceedings of the International Florida Artificial Intelligence Research Society ConferencePrior research showed the instability of word embeddings. That is, the neighborhoods of word vectors differ depending on corpora and training methods.
Anurag Naren Kallakunta +1 more
doaj +1 more source
Advanced Materials, EarlyView.AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll +19 more
wiley +1 more source
Transformer based contextualization of pre-trained word embeddings for irony detection in Twitter
, 2020 José Ángel González +2 more
openalex +2 more sources
Advanced Materials, EarlyView.This study demonstrates a self‐assembly process to generate free‐standing piezoelectric nanomembranes, forming ultracompact microtubular acoustic wave sensors and actuators. The miniaturized 3D piezoelectric platform reported in this work can be applied in telecommunication, energy harvesting, and acoustofluidics. Moreover, the 3D self‐assembly can add
Raphaël C. L‐M. Doineau +9 more
wiley +1 more source
Poincar�� GloVe: Hyperbolic Word Embeddings
, 2018 Words are not created equal. In fact, they form an aristocratic graph with a latent hierarchical structure that the next generation of unsupervised learned word embeddings should reveal. In this paper, justified by the notion of delta-hyperbolicity or tree-likeliness of a space, we propose to embed words in a Cartesian product of hyperbolic spaces ...
Tifrea, Alexandru +2 more
openaire +2 more sources
Advanced Materials, EarlyView.Drawing inspiration from the layered hard‐soft architecture found in sea sponges, this work establishes a new framework for architected cementitious composites (ACC) through multi‐material additive manufacturing (MMAM) process. The integration of mortar and elastomer phases into layered architectures enables synergistic toughening mechanisms, including
Aimane Najmeddine +5 more
wiley +1 more source
Analyzing the Limitations of Cross-lingual Word Embedding Mappings [PDF]
, 2019 Aitor Ormazabal +4 more
openalex +1 more source
Emotional Embeddings: Refining Word Embeddings to Capture Emotional Content of Words
, 2019 Word embeddings are one of the most useful tools in any modern natural language processing expert's toolkit. They contain various types of information about each word which makes them the best way to represent the terms in any NLP task. But there are some types of information that cannot be learned by these models.
Seyeditabari, Armin +3 more
openaire +2 more sources