Results 31 to 40 of about 4,775 (181)
OLSS-Mamba: Order-Aware Low-Rank Spectral–Spatial Mamba for Hyperspectral Image Classification
Hyperspectral image (HSI) classification requires effective spectral–spatial representation learning under limited labeled samples and constrained computational resources.
Chunchao Li +5 more
doaj +1 more source
ABSTRACT Inverse problems in pharmacometrics and quantitative systems pharmacology (QSP) often involve sparse, noisy data, limited measurable states, and complex dynamical systems. Traditional parameter estimation methods can struggle with ill‐posed problems, stiffness, discontinuities, and gray‐box scenarios where only part of the system dynamics is ...
Nazanin Ahmadi Daryakenari +1 more
wiley +1 more source
SambaMixer: State of Health Prediction of Li-Ion Batteries Using Mamba State Space Models
The state of health (SOH) of a Li-ion battery is determined by complex interactions among its internal components and external factors. Approaches leveraging deep learning architectures have been proposed to predict the SOH using convolutional networks ...
Jose Ignacio Olalde-Verano +3 more
doaj +1 more source
Irregular and asynchronous event sequences are prevalent in many domains, such as social media, finance, and healthcare. Traditional temporal point processes (TPPs), like Hawkes processes, often struggle to model mutual inhibition and nonlinearity effectively.
Anningzhe Gao, Shan Dai, Yan Hu
openaire +2 more sources
β‐Cyclodextrin‐functionalized geophagic clay was applied in a fixed‐bed column for the removal of rhodamine B (RhB) and methyl orange (MO). RhB interacts via electrostatic attraction and hydrogen bonding, while MO undergoes cavity inclusion complexation and hydrogen bonding within the βCD structure.
Nomcebo P. Khumalo +2 more
wiley +1 more source
A seismic random noise suppression method based on CNN-Mamba
BackgroundSeismic random noise suppression is recognized as a key step to improve the quality of seismic data. Data-driven deep learning provides an intelligent solution for the noise suppression.
Xiujuan WEI, Xingye LIU, Huailai ZHOU
doaj +1 more source
Infrared‐Guided Super‐Resolution of Remotely Sensed Passive Microwave Sea Surface Temperature
Abstract High‐resolution sea surface temperature (SST) is essential for weather forecasting and climate applications. Passive microwave (MW) SST offers largely cloud‐penetrating coverage but is coarse and spatially smoothed, whereas infrared (IR) SST resolves fine‐scale structures but is frequently cloud‐obscured.
Wenjie Zhou, Xiaofeng Yang
wiley +1 more source
Mamba-based vision models have gained extensive attention as a result of being computationally more efficient than attention-based models. However, spatial redundancy still exists in these models, represented by token and block redundancy. For token redundancy, we analytically find that early token pruning methods will result in inconsistency between ...
Mengxuan Wu +11 more
openaire +2 more sources
Bitemporal Remote Sensing Change Detection With State-Space Models
Change detection in very-high-resolution remote sensing images has gained significant attention, particularly with the rise of deep learning techniques such as convolutional neural networks and Transformers.
Lukun Wang +6 more
doaj +1 more source
Machine learning we can trust: tensor algebra and the design of reliable foundation models
Abstract When an AI model answers our question, can we interrogate this particular answer and receive solid reasoning? Twenty‐four centuries ago, Socrates judged understanding not by how fluently someone spoke but by whether their claims survived questioning.
Grigorios G. Chrysos
wiley +1 more source

