Results 131 to 140 of about 7,883,935 (303)

Scale Is Not All You Need: Revisiting the Biomimetic Roots of Deep Learning to Overcome Fundamental Limitations

IEEE Access
Deep Learning has historically drawn direct inspiration from nature, with Artificial Neural Networks initially grounded in neurobiological principles.
Malek Wahidi, Anthony Rizk, Rodrigue Imad   +2 more
doaj   +1 more source

Entity Search Based on the Representation Learning Model With Different Embedding Strategies

IEEE Access, 2017
We focus on the problem of learning distributed representations for entity search queries, named entities, and their short descriptions. With our representation learning models, the entity search query, named entity, and description can be represented as
Shijia E., Yang Xiang
doaj   +1 more source

RNA Sequencing Resolves Cryptic Pathogenic Variants in Mitochondrial Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Mitochondrial diseases are the most common inherited metabolic disorders, characterized by pronounced clinical and genetic heterogeneity that complicates molecular diagnosis. Although DNA‐based sequencing approaches have become standard in genetic testing, up to half of patients remain without a definitive diagnosis.
Zhimei Liu, Xin Duan, Fatemeh Peymani, Jia Wang, Chengjia Bao, Chaolong Xu, Ying Zou, Zixuan Zhang, Yunxi Zhang, Tongyue Li, Martin Pavlov, Junling Wang, Minhan Song, Tianyu Song, Xiaodi Han, Mingxi Sun, Danmin Shen, Ruoyu Duan, Huafang Jiang, Manting Xu, Holger Prokisch, Fang Fang   +21 more
wiley   +1 more source

Knowledge Representation for Adaptive Learning Design [PDF]

, 2006
Please, cite this publication as: Kravcik, M. & Gasevic, D. (2006). Knowledge Representation for Adaptive Learning Design. Proceedings of Adaptive Hypermedia. June, Dublin, Ireland.
Gasevic, Dragan, Kravcik, Milos
core   +1 more source

What Makes Better Augmentation Strategies? Augment Difficult but Not too Different

, 2022
1
Jaehyung Kim, Dongyeop Kang, Jinwoo Shin, AHN, SUNGSOO   +3 more
core  

Scalable and Efficient Protein Secondary Structure Prediction Using Autoencoder-Reduced ProtBERT Embeddings

Applied Sciences
This study proposes a deep learning framework for Protein Secondary Structure Prediction (PSSP) that prioritizes computational efficiency while preserving classification accuracy.
Yahya Najib Hamood Al-Shameri, İrfan Kösesoy, Hakan Gündüz, Ömer Faruk Yılmaz   +3 more
doaj   +1 more source

Learning Transferable Representations

, 2019
A first contribution of this thesis is to propose causality as a language for problems of distribution shift. First, we consider domain generalisation, where no data from the test distribution are observed during training. What assumptions can be made regarding the relation between train and test distributions for transfer to succeed?
openaire   +3 more sources

Comparing the Effect of Semi‐Immersive Virtual Reality, Computerized Cognitive Training, and Traditional Rehabilitation on Cognitive Function in Multiple Sclerosis: A Randomized Clinical Trial

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, Desiree Latella, Lilla Bonanno, Paulo Cezar Rocha dos Santos, Marcos Maldonado‐Díaz, Meir Plotnik, Rosaria De Luca, Angelo Quartarone, Rocco Salvatore Calabrò   +8 more
wiley   +1 more source

Multilevel Context Learning with Large Language Models for Text-Attributed Graphs on Social Networks

Entropy
There are complex graph structures and rich textual information on social networks. Text provides important information for various tasks, while graph structures offer multilevel context for the semantics of the text.
Xiaokang Cai, Ruoyuan Gong, Hao Jiang
doaj   +1 more source

Memory and Resting‐State Connectivity in Acute Transient Global Amnesia: A Case–Control fMRI Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background and Objectives Transient global amnesia (TGA) is a striking model of isolated amnesia. While hippocampal lesions are well described, the network‐level mechanisms and the precise neuropsychological profile remain debated. Our objective was thus to characterize functional and neuropsychological correlates of acute TGA and their ...
Elias El Otmani, Emmanuel Barbeau, Béatrice Lemesle, Emilie Milongo‐Rigal, Sophie Fernandez, Sandrine Charpentier, Jean‐François Albucher, Nicolas Raposo, Fabrice Bonneville, Patrice Péran, Jérémie Pariente   +10 more
wiley   +1 more source