Results 61 to 70 of about 1,159,266 (295)
Liver organoids: modelling complexity in homeostasis and disease
FEBS Letters, EarlyView.Studying liver in vitro has been challenging because simple 2D cell cultures fail to capture liver's cellular and architectural complexity. To bridge this gap, scientists increasingly use organoids, 3D liver models which better mimic liver composition and function. This review examines recent advances in liver organoid complexity and realism, discusses
Anna M. Dowbaj, Meritxell Huch
wiley +1 more source
sentiment specific word embedding
, 2018 <p>sentiment specific word embedding learned based on the approach described in the following paper:</p> <p>D. Tang, et al., Learning Sentiment-Specific Word Embedding for Twitter Sentiment Classification, ACL 2014< ...
Tang
core +1 more source
New Directions for Adult and Continuing Education, EarlyView.ABSTRACT Advancing artificial intelligence (AI) has transformed learning and work, yet higher education and professional development programs have not systematically equipped learners for AI‐prevalent environments. This lack of preparation creates uncertainty regarding control, responsibility, trust, and accountability.
Moon‐Heum Cho, Jerusalem Merkebu
wiley +1 more source
Future Internet, 2018 Chinese event extraction uses word embedding to capture similarity, but suffers when handling previously unseen or rare words. From the test, we know that characters may provide some information that we cannot obtain in words, so we propose a novel ...
Yue Wu, Junyi Zhang
doaj +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Cognitive impairment is a common non‐motor symptom in Multiple Sclerosis (MS), negatively affecting autonomy and Quality of Life (QoL). Innovative rehabilitation strategies, such as semi‐immersive virtual reality (VR) and computerized cognitive training (CCT), may offer advantages over traditional cognitive rehabilitation (TCR ...
Maria Grazia Maggio +8 more
wiley +1 more source
Word Activation Forces Map Word Networks [PDF]
, 2011 Words associate with each other in a manner of intricate clusters^1-3^. Yet the brain capably encodes the complex relations into workable networks^4-7^ such that the onset of a word in the brain automatically and selectively activates its associates ...
Jun Guo, Hanliang Guo, Zhanyi Wang
core
Word Embedding with Neural Probabilistic Prior
, 2023 To improve word representation learning, we propose a probabilistic prior which can be seamlessly integrated with word embedding models. Different from previous methods, word embedding is taken as a probabilistic generative model, and it enables us to ...
Li, Ping, Li, Dingcheng, Ren, Shaogang
core
A Smaller and Better Word Embedding for Neural Machine Translation
IEEE Access, 2023 Word embeddings play an important role in Neural Machine Translation (NMT). However, it still has a series of problems such as ignoring the prior knowledge of the association between words, relying on specific task constraints passively in parameter ...
Qi Chen
doaj +1 more source
Spoken-Word Recognition: The Access to Embedded Words
Brain and Language, 1999 Two cross-modal priming experiments investigated whether the representation of either an initial- or a final-embedded word may be activated when the longer carrier word is auditorily presented. Visual targets were semantically related either to the embedded word or to the carrier word or they were unrelated to the primes. A priming effect was found for
Isel, F., Bacri, N.
openaire +3 more sources
A Joint Model for Word Embedding and Word Morphology [PDF]
Proceedings of the 1st Workshop on Representation Learning for NLP, 2016 This paper presents a joint model for performing unsupervised morphological analysis on words, and learning a character-level composition function from morphemes to word embeddings. Our model splits individual words into segments, and weights each segment according to its ability to predict context words.
Rei, Marek, Cao, Kris
openaire +4 more sources