Graph representation learning - Open Access .click

Results 241 to 250 of about 8,038,825 (297)

Single-step retrosynthesis prediction via multitask graph representation learning. [PDF]

Nat Commun
Zhao PC +7 more
europepmc +1 more source

Nonreciprocal Swarmalators With Reconfigurable and Controllable Formations for Robot Collectives

Advanced Robotics Research, EarlyView.
Nonreciprocal swarmalator interactions are enabled through control barrier functions to transform self‐organizing robot collectives into reconfigurable, constraint‐aware systems. Complex two‐ and three‐dimensional shapes, continuous morphing, obstacle‐aware navigation, collective splitting, and object transport emerge from modulating agent‐level ...
Kush Patel, Xinyue Xu, Wei Xiao, Steven Ceron +3 more
wiley +1 more source

Multi-Label Feature Selection with Feature-Label Subgraph Association and Graph Representation Learning. [PDF]

Entropy (Basel)
Ruan J, Wang M, Liu D, Chen M, Gao X.
europepmc +1 more source

Deep Contrastive Learning for High‐Throughput Prediction of Drug Resistance Mutations from Sequences

Advanced Science, EarlyView.
This study presents DeepMutDTA, a deep learning framework aimed at predicting mutation‐induced changes in protein‐drug interactions and prioritizing variants potentially linked to drug resistance. Trained on large‐scale data, it incorporates SimSiam‐MuTF, a label‐aware contrastive fine‐tuning strategy that encourages separation between WT and MT ...
Xiaowen Hu +7 more
wiley +1 more source

TP-RotatE: A knowledge graph representation learning method combining path information and rules to capture complex relational patterns. [PDF]

PLoS One
Liu X, Shi Y, Xu Y, Ren Y.
europepmc +1 more source

In Situ X‐Ray Tomography and Acoustic Emission Monitoring of Damage Evolution in C/C‐SiC Composites Fabricated by Liquid Silicon Infiltration

Advanced Science, EarlyView.
This study investigates how the internal structure of fiber‐reinforced ceramic composites affects their resistance to damage. By combining 3D X‐ray imaging with acoustic emission monitoring during mechanical testing, it reveals how silicon distribution influences crack formation.
Yang Chen +7 more
wiley +1 more source

An experimental analysis of graph representation learning for Gene Ontology based protein function prediction. [PDF]

PeerJ
Vu TTD, Kim J, Jung J.
europepmc +1 more source

NeuroSuite for Long‐Term Functional and Structural Studies of Air‐Liquid Interface Cerebral Organoids

Advanced Science, EarlyView.
NeuroSuite provides a modular hardware‐software platform integrating Neuroweb and NeuroMaps to enable long‐term, in situ electrophysiological interrogation of air–liquid interface organoid slices while preserving tissue architecture. Its components can be used together or independently to capture real‐time activity, spatial network dynamics, and ...
Belquis Haider +14 more
wiley +1 more source

stHGC: a self-supervised graph representation learning for spatial domain recognition with hybrid graph and spatial regularization. [PDF]

Brief Bioinform
Wang R, Dai Q, Duan X, Zou Q.
europepmc +1 more source

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

Advanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju +5 more
wiley +1 more source

machine learning cs.lg
fos: computer and information sciences
computer science - machine learning

statistics - machine learning
machine learning stat.ml
graph neural networks

social and information networks cs.si
computer science - social and information networks
deep learning