Results 141 to 150 of about 229,000 (311)
FDC-LGL: Fast Discrete Clustering with Local Graph Learning for Large-Scale Datasets
MathematicsGraph-based clustering is a fundamental task in unsupervised machine learning and has been extensively applied to complex data mining scenarios, such as pattern recognition and data classification. However, most existing graph clustering algorithms still
Shenfei Pei, Ruiyu Huang, Zengwei Zheng
doaj +1 more source
Molecular graph contrastive learning with line graph
Pattern RecognitionTrapped by the label scarcity in molecular property prediction and drug design, graph contrastive learning (GCL) came forward. Leading contrastive learning works show two kinds of view generators, that is, random or learnable data corruption and domain knowledge incorporation.
Xueyuan Chen +6 more
openaire +2 more sources
Advanced Functional Materials, EarlyView.Field‐free spin‐orbit torque domain‐wall synapses integrated with stochastic MTJ neurons enable compact hardware Boltzmann machines. Leveraging intrinsic stochasticity and multi‐level conductance, the system achieves efficient probabilistic learning with high accuracy, demonstrating a scalable spintronic platform for energy‐efficient edge AI.
Aijaz H. Lone +8 more
wiley +1 more source
InformationCurrent Facial expression recognition methods typically extract facial features indiscriminately, incorporating expression-irrelevant information that compromises recognition accuracy.
Guanghui Xu +5 more
doaj +1 more source
Toward Fast Proton Shuttling in Acidic Oxygen Evolution Reaction
Advanced Functional Materials, EarlyView.This review establishes proton transfer dynamics as a descriptor governing acidic OER activity, moving beyond the kinetic constraints derived from the proton coupled electron transfer. We discuss how deprotonation governs classical mechanisms, including adsorbate evolution mechanism (AEM), lattice oxygen mechanism (LOM) and oxide path mechanism (OPM ...
Ashish Gaur +3 more
wiley +1 more source
Constructing VEGGIE: Machine Learning for [PDF]
, 2008 Context-sensitive graph grammar construction tools have been used to develop and study interesting languages. However, the high dimensionality of graph grammars result in costly effort for their construction and maintenance.
Context-sensitive Graph Grammars
core
Advanced Healthcare Materials, EarlyView.ABSTRACT Quantitative characterization of vascular heterogeneity in complex microphysiological systems (MPS), particularly within patient‐derived tumor microenvironments, remains a major challenge for scalable disease modeling and therapeutic evaluation.
Jungseub Lee +9 more
wiley +1 more source
Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application
Advanced Materials, EarlyView.This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong +12 more
wiley +1 more source
Predicting Redox Potentials by Graph-Based Machine Learning Methods [PDF]
The evaluation of oxidation and reduction potentials is a pivotal task in various chemical fields. However, their accurate prediction by theoretical computations, which is a complementary task and sometimes the only alternative to experimental ...
Vincent, Tognetti +5 more
core +1 more source
Human learning of hierarchical graphs
Physical Review EHumans are constantly exposed to sequences of events in the environment. Those sequences frequently evince statistical regularities, such as the probabilities with which one event transitions to another. Collectively, inter-event transition probabilities can be modeled as a graph or network.
Xiaohuan Xia +6 more
openaire +4 more sources