Results 61 to 70 of about 79,461 (254)

Multi‐View Biomedical Foundation Models for Molecule‐Target and Property Prediction

Advanced Science, EarlyView.
Molecular foundation models can provide accurate predictions for a large set of downstream tasks. We develop MMELON, an approach that integrates pre‐trained graph, image, and text foundation models and validate our multi‐view model on over 120 tasks, including GPCR binding.
Parthasarathy Suryanarayanan, Yunguang Qiu, Shreyans Sethi, Diwakar Mahajan, Hongyang Li, Yuxin Yang, Elif Eyigoz, Aldo Guzmán‐Sáenz, Daniel E. Platt, Timothy H. Rumbell, Kenney Ng, Sanjoy Dey, Myson Burch, Bum Chul Kwon, Pablo Meyer, Feixiong Cheng, Jianying Hu, Joseph A. Morrone   +17 more
wiley   +1 more source

Estimate Laplacian Spectral Properties of Large-Scale Networks by Random Walks and Graph Transformation

Mathematics
For network graphs, numerous graph features are intimately linked to eigenvalues of the Laplacian matrix, such as connectivity and diameter. Thus, it is very important to solve eigenvalues of the Laplacian matrix for graphs.
Changlei Zhan, Xiangyu Li, Jie Chen
doaj   +1 more source

On the Approximation of Laplacian Eigenvalues in Graph Disaggregation

, 2016
Graph disaggregation is a technique used to address the high cost of computation for power law graphs on parallel processors. The few high-degree vertices are broken into multiple small-degree vertices, in order to allow for more efficient computation in
Hu, Xiaozhe, Urschel, John C., Zikatanov, Ludmil T.   +2 more
core   +1 more source

Split non-threshold Laplacian integral graphs [PDF]

Linear and Multilinear Algebra, 2010
The aim of this article is to answer a question posed by Merris in European Journal of Combinatorics, 24 (2003) pp. 413 − 430, about the possibility of finding split non-threshold graphs that are Laplacian integral, i.e. graphs for which the eigenvalues of the corresponding Laplacian matrix are integers.
Kirkland, Stephen, de Freitas, Maria Aguieiras Alvarez, Del Vecchio, Renata Raposo, de Abreu, Nair Maria Maia   +3 more
openaire   +2 more sources

Feature Selection for Machine Learning‐Driven Accelerated Discovery and Optimization in Emerging Photovoltaics: A Review

Advanced Intelligent Discovery, EarlyView.
Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang, Jiayi Tan, Qizhen Song, Tian Du, Jens Hauch, Christoph J. Brabec   +5 more
wiley   +1 more source

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

Primer for the algebraic geometry of sandpiles [PDF]

, 2011
The Abelian Sandpile Model (ASM) is a game played on a graph realizing the dynamics implicit in the discrete Laplacian matrix of the graph. The purpose of this primer is to apply the theory of lattice ideals from algebraic geometry to the Laplacian ...
Perkinson, David, Perlman, Jacob, Wilmes, John   +2 more
core  

Upsampling DINOv2 Features for Unsupervised Vision Tasks and Weakly Supervised Materials Segmentation

Advanced Intelligent Systems, EarlyView.
Feature from recent image foundation models (DINOv2) are useful for vision tasks (segmentation, object localization) with little or no human input. Once upsampled, they can be used for weakly supervised micrograph segmentation, achieving strong results when compared to classical features (blurs, edge detection) across a range of material systems.
Ronan Docherty, Antonis Vamvakeros, Samuel J. Cooper   +2 more
wiley   +1 more source

On Path Laplacian Eigenvalues and Path Laplacian Energy of Graphs

Journal of New Theory, 2018
We introduce the concept of Path Laplacian Matrix for a graph and explore the eigenvalues of this matrix. The eigenvalues of this matrix are called the path Laplacian eigenvalues of the graph.
Shridhar Chandrakant Patekar, Maruti Mukinda Shikare   +1 more
doaj  

-borderenergetic graphs

AKCE International Journal of Graphs and Combinatorics, 2020
A graph is said to be borderenergetic (-borderenergetic, respectively) if its energy (Laplacian energy, respectively) equals the energy (Laplacian energy, respectively) of the complete graph .
Qingyun Tao, Yaoping Hou
doaj   +1 more source