Results 101 to 110 of about 254,842 (278)
Encoding word order in complex embeddings [PDF]
, 2019 15 pages, 3 figures, ICLR 2020 spotlight paper.
Benyou Wang +5 more
openaire +3 more sources
Hash Embeddings for Efficient Word Representations
, 2017 We present hash embeddings, an efficient method for representing words in a continuous vector form. A hash embedding may be seen as an interpolation between a standard word embedding and a word embedding created using a random hash function (the hashing ...
Hansen, Jonas Meinertz +2 more
core
Conductive Bonding and System Architectures for High‐Performance Flexible Electronics
Advanced Functional Materials, EarlyView.This review outlines bonding technologies and structural design strategies that support high‐performance flexible and stretchable electronics. Bonding approaches such as surface‐activated bonding and anisotropic conductive films, together with system‐level architectures including buffer layers and island‐bridge structures, possess distinct mechanical ...
Kazuma Nakajima, Kenjiro Fukuda
wiley +1 more source
All Word Embeddings from One Embedding
, 2020 NeurIPS ...
Takase, Sho, Kobayashi, Sosuke
openaire +2 more sources
Advanced Functional Materials, EarlyView.A pixelation‐free, monolithic iontronic pressure sensor enables simultaneous pressure and position sensing over large areas. AC‐driven ion release generates spatially varying impedance pathways depending on the pressure. Machine learning algorithms effectively decouple overlapping pressure–position signals from the multichannel outputs, achieving high ...
Juhui Kim +10 more
wiley +1 more source
A Study on Word2Vec on a Historical Swedish Newspaper Corpus
Digital Humanities in the Nordic and Baltic Countries Publications, 2018 Detecting word sense changes can be of great interest in the field of digital humanities. Thus far, most investigations and automatic methods have been developed and carried out on English text and most recent methods make use of word embeddings.
Nina Tahmasebi
doaj +1 more source
Deconstructing Word Embeddings
, 2019 A review of Word Embedding Models through a deconstructive approach reveals their several shortcomings and inconsistencies. These include instability of the vector representations, a distorted analogical reasoning, geometric incompatibility with linguistic features, and the inconsistencies in the corpus data.
openaire +2 more sources
Gourd‐Inspired Design of Unit Cell with Multiple Gradients for Physiological‐Range Pressure Sensing
Advanced Functional Materials, EarlyView.Gourd‐shaped micro‐dome arrays with coordinated modulus, conductivity, and geometric gradients co‐optimize sensitivity and linearity in piezoresistive tactile sensors. Under pressure, a solid upper dome embeds into a porous lower dome, triggering rapid contact‐area growth and series‐to‐parallel conduction, enabling unsaturated, intensity‐resolved ...
Jiayi Xu +6 more
wiley +1 more source
Advanced Functional Materials, EarlyView.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
IEEE AccessDiversity in use of Question and Answering (Q/A) is evolving as a popular application in the area of Natural Language Processing (NLP). The alive unsupervised word embedding approaches are efficient to collect Latent-Semantic data on number of tasks. But
M. Suguna, K. S. Sakunthala Prabha
doaj +1 more source