Results 41 to 50 of about 665 (142)

Hypergraph spectral clustering via sample self-representation

, 2016
Traditional clustering methods cluster data with pairwise graph and usually result in information loss. In this paper, we propose a novel spectral clustering method by combing hypergraph and sample self-representation together.
Zhang, S., Deng, Z., Li, Y., Cheng, D.
core   +1 more source

Lightweight Hybrid Wafer Defect Pattern Network Based on Feedforward Efficient Attention

CAAI Transactions on Intelligence Technology, Volume 11, Issue 1, Page 149-166, February 2026.
ABSTRACT With the increase of semiconductor integration density, in order to cope with the increase of wafer defect complexity and types, especially the low recognition accuracy of overlapping mixed defects and unknown wafer defects, this study proposes a lightweight model for wafer defect detection called LightWMNet.
Zhiqiang Hu, Yiquan Wu
wiley   +1 more source

Nearly Hamilton cycles in sublinear expanders and applications

Journal of the London Mathematical Society, Volume 113, Issue 2, February 2026.
Abstract We develop novel methods for constructing nearly Hamilton cycles in sublinear expanders with good regularity properties, as well as new techniques for finding such expanders in general graphs. These methods are of independent interest due to their potential for various applications to embedding problems in sparse graphs.
Shoham Letzter, Abhishek Methuku, Benny Sudakov   +2 more
wiley   +1 more source

Equivariant Hypergraph Neural Networks

, 2022
Many problems in computer vision and machine learning can be cast as learning on hypergraphs that represent higher-order relations. Recent approaches for hypergraph learning extend graph neural networks based on message passing, which is simple yet ...
Cho, Sungjun, Oh, Saeyoon, Hong, Seunghoon, Kim, Jinwoo   +3 more
core   +1 more source

Counting Independent Sets in Percolated Graphs via the Ising Model

Random Structures &Algorithms, Volume 68, Issue 1, January 2026.
ABSTRACT Given a graph G$$ G $$, we form a random subgraph Gp$$ {G}_p $$ by including each edge of G$$ G $$ independently with probability p$$ p $$. We provide an asymptotic expansion of the expected number of independent sets in random subgraphs of regular bipartite graphs satisfying certain vertex‐isoperimetric properties, extending the work of ...
Anna Geisler, Mihyun Kang, Michail Sarantis, Ronen Wdowinski   +3 more
wiley   +1 more source

Intelligent Fault Diagnosis Method Based on Hybrid Attention and Dimension‐Aligned Distillation for Rotating Machinery

IET Signal Processing, Volume 2026, Issue 1, 2026.
Intelligent fault diagnosis (IFD) of rotating machinery is critical for ensuring industrial safety and reliability. However, existing deep learning‐based IFD methods face three core challenges: suboptimal feature discrimination of single attention mechanisms, high computational cost limiting edge deployment, and class imbalance bias leading to ...
Chuanyan Wu, Zhiguo Yu, Bentao Lin, Biao Yu, Qinyu Jiang, Huanghe Zhang, Rui Gao, Qifan Yang, Rui Song, Junlin Hu   +9 more
wiley   +1 more source

Hypergraph Partitioning With Embeddings

, 2020
Problems in scientific computing, such as distributing large sparse matrix operations, have analogous formulations as hypergraph partitioning problems. A hypergraph is a generalization of a traditional graph wherein "hyperedges" may connect any number of
Safro, Ilya, Sybrandt, Justin, Shaydulin, Ruslan   +2 more
core   +1 more source

A Hybrid Deep Learning Framework for Early Detection of Ovarian Cancer Using Ultrasound and MRI Images on a Secure Cloud Platform

Complexity, Volume 2026, Issue 1, 2026.
Ovarian cancer continues to pose a major diagnostic challenge, as early‐stage disease often presents with subtle and heterogeneous imaging characteristics that limit the effectiveness of single‐modality analysis. In response to this challenge, this study proposes a novel hybrid deep learning framework for the early detection and classification of ...
Umesh Kumar Lilhore, Vanusha D., Srilatha Gundapaneni, Anto Lourdu Xavier Raj Arockia Selvarathinam, Rasmi A., Sarita Simaiya, Lidia Gosy Tekeste, Ehab Seif Ghith, Heba G. Mohamed, Raul Alcaraz Martinez   +9 more
wiley   +1 more source

Integration of Digital Twin Technology in Orthodontics: A Scoping Review

International Journal of Dentistry, Volume 2026, Issue 1, 2026.
Background Digital twin technology (DTT) is an emerging concept in healthcare enabling real‐time patient and process simulations and predictive analytics that enhance personalized treatment and clinical decision‐making. Orthodontics, being a comprehensive subject involving technicalities associated with diagnosis and treatment planning, the specific ...
Isha Bhardwaj, Nidhin Philip Jose, Supriya Nambiar, Dhruv Ahuja, Shushma Rao, Sabarinath Prasad, Nicola Alberto Valente   +6 more
wiley   +1 more source

Multimodal Data Fusion Algorithm Based on Hypergraph Regularization

, 2023
The multi-modal data fusion improves the performance of data classification and prediction by learning the correlation information and complementary information between multiple datasets.However,existing data fusion methods are based on feature pattern ...
CUI Bingjing, ZHANG Yipu, WANG Biao
core   +1 more source