Results 91 to 100 of about 115,711 (260)
Domain-Invariant Label Propagation With Adaptive Graph Regularization
IEEE AccessAs an effective machine learning paradigm, domain adaptation (DA) learning aims to enhance the learning performance of the target domain by utilizing other relevant but distinct domain(s) (referred to as the source domain(s)).
Yanning Zhang, Jianwen Tao, Liangda Yan
doaj +1 more source
Scrambling‐Enhanced Quantum Battery Charging in Black Hole Analogues
Advanced Science, EarlyView.By employing a black‐hole‐analog quantum battery constructed from a position‐dependent XY model, its dynamical behavior is investigated through a quench of the scrambling parameter. It is systematically quantified that how the simulated scrambling improves key performance metrics‐namely, stored energy, peak power, and charging time‐thereby offering a ...
Zhilong Liu +3 more
wiley +1 more source
Distance-Regular Graphs and Halved Graphs
European Journal of Combinatorics, 1986 Let G be a bipartite distance-regular graph with bipartition \(V(G)=X\cup Y\). Let \(V(G')=X\) and, for x and y in X, let x be adjacent to y in G' if and only if x is of distance two from y in G. Then G' is called a halved graph of G, and is distance-regular. This paper discusses whether G' is one of the known, large-diameter, distance-regular graphs.
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Advanced Science, EarlyView.SAGE is a unified framework for spatial domain identification in spatial transcriptomics that jointly models tissue architecture and gene programs. Topic‐driven gene selection (NMF plus classifier‐based scoring) highlights spatially informative genes, while dual‐view graph embedding fuses local expression and non‐local functional relations.
Yi He +5 more
wiley +1 more source
Advanced Science, EarlyView.This study introduces stVGP, a variational spatial Gaussian process framework for multi‐modal, multi‐slice spatial transcriptomics. By integrating histological and genomic data through hybrid alignment and attention‐based fusion, stVGP reconstructs coherent 3D functional landscapes.
Zedong Wang +3 more
wiley +1 more source
High‐Conductivity Electrolytes Screened Using Fragment‐ and Composition‐Aware Deep Learning
Advanced Science, EarlyView.We present a new deep learning framework that hierarchically links molecular and functional unit attributions to predict electrolyte conductivity. By integrating molecular composition, ratios, and physicochemical descriptors, it achieves accurate, interpretable predictions and large‐scale virtual screening, offering chemically meaningful insights for ...
Xiangwen Wang +6 more
wiley +1 more source
TorusE: Knowledge Graph Embedding on a Lie Group
, 2017 Knowledge graphs are useful for many artificial intelligence (AI) tasks. However, knowledge graphs often have missing facts. To populate the graphs, knowledge graph embedding models have been developed.
Ebisu, Takuma, Ichise, Ryutaro
core +1 more source
Advanced Science, EarlyView.By combining ionic nonvolatile memories and transistors, this work proposes a compact synaptic unit to enable low‐precision neural network training. The design supports in situ weight quantization without extra programming and achieves accuracy comparable to ideal methods. This work obtains energy consumption advantage of 25.51× (ECRAM) and 4.84× (RRAM)
Zhen Yang +9 more
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Journal of Combinatorial Theory, Series B, 1983 AbstractTriples (p, n, r) for which there exists an r-regular Kn-free graph on p points are determined.
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Advanced Electronic Materials, EarlyView.A lead‐free perovskite memristive solar cell structure that call emulate both synaptic and neuronal functions controlled by light and electric fields depending on top electrode type. ABSTRACT Memristive devices based on halide perovskites hold strong promise to provide energy‐efficient systems for the Internet of Things (IoT); however, lead (Pb ...
Michalis Loizos +4 more
wiley +1 more source