Results 41 to 50 of about 5,906,664 (269)
Organoids in pediatric cancer research
FEBS Letters, EarlyView.Organoid technology has revolutionized cancer research, yet its application in pediatric oncology remains limited. Recent advances have enabled the development of pediatric tumor organoids, offering new insights into disease biology, treatment response, and interactions with the tumor microenvironment.
Carla Ríos Arceo, Jarno Drost
wiley +1 more source
Centered Self-attention Layers
The self-attention mechanism in transformers and the message-passing mechanism in graph neural networks are repeatedly applied within deep learning architectures. We show that this application inevitably leads to oversmoothing, i.e., to similar representations at the deeper layers for different tokens in transformers and different nodes in graph neural
Ameen Ali, Tomer Galanti, Lior Wolf
openaire +2 more sources
Reciprocal control of viral infection and phosphoinositide dynamics
FEBS Letters, EarlyView.Phosphoinositides, although scarce, regulate key cellular processes, including membrane dynamics and signaling. Viruses exploit these lipids to support their entry, replication, assembly, and egress. The central role of phosphoinositides in infection highlights phosphoinositide metabolism as a promising antiviral target.
Marie Déborah Bancilhon, Bruno Mesmin
wiley +1 more source
Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system
FEBS Letters, EarlyView.Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley +1 more source
A Self-Attentive model for Knowledge Tracing
CoRR, 2019 International Conference on Education Data ...
Shalini Pandey, George Karypis
openaire +3 more sources
FEBS Letters, EarlyView.Embryo‐like structures (stembryos) are an innovative tool, but they are hindered by experimental variability and limited developmental potential. DNA methylation is crucial for mammalian development, but its status in stembryo models is poorly characterized.
Sara Canil +4 more
wiley +1 more source
, 2023 Extracting rich feature representations is a key challenge in person re-identification (Re-ID) tasks. However, traditional Convolutional Neural Networks (CNN) based methods could ignore a part of information when processing local regions of person images,
Wei Hou (48073), Yinghua Zhang (122625)
core +1 more source
CoRRWe introduce exclusive self attention (XSA), a simple modification of self attention (SA) that improves Transformer's sequence modeling performance. The key idea is to constrain attention to capture only information orthogonal to the token's own value vector (thus excluding information of self position), encouraging better context modeling.
openaire +2 more sources
A Structured Self-attentive Sentence Embedding
CoRR, 2017 This paper proposes a new model for extracting an interpretable sentence embedding by introducing self-attention. Instead of using a vector, we use a 2-D matrix to represent the embedding, with each row of the matrix attending on a different part of the sentence. We also propose a self-attention mechanism and a special regularization term for the model.
Zhouhan Lin +6 more
openaire +3 more sources
Self-attentive Biaffine Dependency Parsing [PDF]
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019 The current state-of-the-art dependency parsing approaches employ BiLSTMs to encode input sentences.Motivated by the success of the transformer-based machine translation, this work for the first time applies the self-attention mechanism to dependency parsing as the replacement of the BiLSTM-based encoders, leading to competitive performance on both ...
Ying Li 0065 +5 more
openaire +1 more source