Results 141 to 150 of about 73,165 (262)
Initial State Privacy of Nonlinear Systems on Riemannian Manifolds
International Journal of Robust and Nonlinear Control, EarlyView.ABSTRACT In this paper, we investigate initial state privacy protection for discrete‐time nonlinear closed systems. By capturing Riemannian geometric structures inherent in such privacy challenges, we refine the concept of differential privacy through the introduction of an initial state adjacency set based on Riemannian distances.
Le Liu, Yu Kawano, Antai Xie, Ming Cao
wiley +1 more source
Remarks on comparison principles for -Laplacian with extension to -Laplacian
Our purpose is to generalize some recent comparison principles for operators driven by [Formula: see text]-Laplacian to a wide class of quasilinear equations including [Formula: see text]-Laplacian.
Ahmed Mohammed, Antonio Vitolo
core +1 more source
Remote Sensing in Ecology and Conservation, EarlyView.This study evaluates the performances of synchronous aerial visible (VIS) and thermal infrared (TIR) imagery for detecting great blue heron (Ardea herodias) nests and individuals using a YOLO11n model. VIS and TIR images were automatically aligned using deep learning, and both early and late fusion approaches were tested.
Camille Dionne‐Pierre +6 more
wiley +1 more source
Small, EarlyView.Structure‐guided internal twin‐Strep tagging of the tetraspanins CD63 or CD9 enables rapid and efficient antibody‐free affinity isolation of engineered extracellular vesicles (EVs) using Strep technology while allowing luminal protein loading. The approach removes over 96% of contaminants, separates tagged EVs from coexisting viral particles, and ...
Minh‐Tu Pham +14 more
wiley +1 more source
Against All Odds?—A Surprisingly Not So Easy Dice Game
Teaching Statistics, EarlyView.ABSTRACT A game with 11 players, 2 dice, and simple rules. However, it turns out that the best strategy is not only absent from the literature, but that misconceptions about winning strategies also prevail among surveyed students. This makes it all the more surprising that it is not so easy to get to the bottom of the game mathematically.
Christoph Oberbucher +1 more
wiley +1 more source
CAAI Transactions on Intelligence Technology, EarlyView.Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma +4 more
wiley +1 more source
Enhancing generalized spectral clustering with embedding Laplacian graph regularization
CAAI Transactions on Intelligence Technology, EarlyView.Abstract An enhanced generalised spectral clustering framework that addresses the limitations of existing methods by incorporating the Laplacian graph and group effect into a regularisation term is presented. By doing so, the framework significantly enhances discrimination power and proves highly effective in handling noisy data.
Hengmin Zhang +5 more
wiley +1 more source
Persistent Local Laplacian Prediction of Protein-Ligand Binding Affinities. [PDF]
J Chem Inf ModelLiu J, Feng H.
europepmc +1 more source
Boosted unsupervised feature selection for tumor gene expression profiles
CAAI Transactions on Intelligence Technology, EarlyView.Abstract In an unsupervised scenario, it is challenging but essential to eliminate noise and redundant features for tumour gene expression profiles. However, the current unsupervised feature selection methods treat all samples equally, which tend to learn discriminative features from simple samples.
Yifan Shi +5 more
wiley +1 more source
Spectral Characterization of Stochastic Epidemic Variability on Regular Networks via the Kirchhoff Index. [PDF]
Entropy (Basel)Alnafisah Y, Sohaly MA.
europepmc +1 more source