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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5 6 7 8...78 Hits 61 – 80 of 1.552 61 Multi-lingual character handwriting framework based on an integrated deep learning based sequence-to-sequence attention model Rabhi, Besma; Elbaati, Abdelkarim; Boubaker, Houcine. - : Springer, 2021 BASE Show details 62 DEV - Development of Temporal Visual Selective Attention in Deaf Children ... Terhune-Cotter, Brennan. - : Open Science Framework, 2021 BASE Show details 63 Age of Acquisition Effects on the decomposition of compound words ... Elsherif, Mahmoud. - : Open Science Framework, 2021 BASE Show details 64 SANKAT PRADATA AUR JANATA. ... Tomar, Neetusingh. - : figshare, 2021 BASE Show details 65 SANKAT PRADATA AUR JANATA. ... Tomar, Neetusingh. - : figshare, 2021 BASE Show details 66 SANKAT PRADATA AUR JANATA. ... Tomar, Neetusingh. - : figshare, 2021 BASE Show details 67 SANKAT PRADATA AUR JANATA. ... Tomar, Neetusingh. - : figshare, 2021 BASE Show details 68 Supervised attention from natural language feedback for reinforcement learning ... Cannon, Clara Cecilia. - : The University of Texas at Austin, 2021 BASE Show details 69 Comparing Encoder-Decoder Architectures for Neural Machine Translation: A Challenge Set Approach ... Doan, Coraline. - : Université d'Ottawa / University of Ottawa, 2021 BASE Show details 70 The time course of word imageability processing and its interaction with external visual sensory input ... Filip, Maroš. - : Open Science Framework, 2021 BASE Show details 71 Auditory distraction while reading in different languages ... Ríos López, Paula. - : Open Science Framework, 2021 BASE Show details 72 Influence of encoding difficulty, word frequency, and phonological regularity on age differences in word naming. Madden, David J; Allen, Philip A; Bucur, Barbara. - : Informa UK Limited, 2021 BASE Show details 73 Multisensory integration-attention trade-off in cochlear-implanted deaf individuals ... van de Rijt, Luuk P.H.; Opstal, John; Wanrooij, Marc. - : Radboud University, 2021 BASE Show details 74 Sustained attention across toddlerhood: The roles of language and sleep Rudasill, Kathleen M.; Bates, John E.; Hoyniak, Caroline P.... In: Faculty Scholarship 2021 (2021) BASE Show details 75 Engagement of Language and Domain General Networks during Word Monitoring in a Native and Unknown Language Kelly Cotosck; Jed Meltzer; Mariana Nucci... In: Brain Sciences ; Volume 11 ; Issue 8 (2021) BASE Show details 76 KGGCN: Knowledge-Guided Graph Convolutional Networks for Distantly Supervised Relation Extraction Ningyi Mao; Wenti Huang; Hai Zhong In: Applied Sciences ; Volume 11 ; Issue 16 (2021) Abstract: Distantly supervised relation extraction is the most popular technique for identifying semantic relation between two entities. Most prior models only focus on the supervision information present in training sentences. In addition to training sentences, external lexical resource and knowledge graphs often contain other relevant prior knowledge. However, relation extraction models usually ignore such readily available information. Moreover, previous works only utilize a selective attention mechanism over sentences to alleviate the impact of noise, they lack the consideration of the implicit interaction between sentences with relation facts. In this paper, (1) a knowledge-guided graph convolutional network is proposed based on the word-level attention mechanism to encode the sentences. It can capture the key words and cue phrases to generate expressive sentence-level features by attending to the relation indicators obtained from the external lexical resource. (2) A knowledge-guided sentence selector is proposed, which explores the semantic and structural information of triples from knowledge graph as sentence-level knowledge attention to distinguish the importance of each individual sentence. Experimental results on two widely used datasets, NYT-FB and GDS, show that our approach is able to efficiently use the prior knowledge from the external lexical resource and knowledge graph to enhance the performance of distantly supervised relation extraction. Keyword: attention mechanism; graph convolutional network; knowledge graph embedding; relation extraction URL: https://doi.org/10.3390/app11167734 BASE Hide details 77 Predictions about the Cognitive Consequences of Language Switching on Executive Functioning Inspired by the Adaptive Control Hypothesis Fail More Often than Not Kenneth R. Paap; Lauren Mason; Regina Anders-Jefferson In: Brain Sciences ; Volume 11 ; Issue 9 (2021) BASE Show details 78 Communication Styles and Attention Performance in Primary School Children Gabriel G. de la Torre; Miguel A. Ramallo; Sara Gonzalez-Torre; Alvaro Mora Prat; Andrea Rueda-Marroquin; Amanda Sallago-Marcos; Zoraida Toro-Barrios; Manuel A. Garcia In: Behavioral Sciences; Volume 11; Issue 12; Pages: 172 (2021) BASE Show details 79 MRE: A Military Relation Extraction Model Based on BiGRU and Multi-Head Attention Yiwei Lu; Ruopeng Yang; Xuping Jiang... In: Symmetry ; Volume 13 ; Issue 9 (2021) BASE Show details 80 Closed-Loop Cognitive-Driven Gain Control of Competing Sounds Using Auditory Attention Decoding Ali Aroudi; Eghart Fischer; Maja Serman... In: Algorithms ; Volume 14 ; Issue 10 (2021) BASE Show details Page: 1 2 3 4 5 6 7 8...78

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