Results 191 to 200 of about 7,883,935 (303)

Concept-aware contrastive representation learning for cross-translation semantic consistency modeling of the Analects. [PDF]

PLoS One
He T, Dai P, Wang R, Zhao Y, Zhao C.
europepmc   +1 more source

Multimodal representation and learning.

, 2019
Recent years have seen an explosion in multimodal data on the web. It is therefore important to perform multimodal learning to understand the web. However, it is challenging to join various modalities because each modality has a different representation and correlational structure.
openaire   +2 more sources

Extending Service Beyond Active Duty: Generalizability of Rheumatoid Arthritis Research Conducted Among U.S. Veterans

Arthritis Care &Research, Accepted Article.
Biomedical research involving United States Veterans continues to advance healthcare beyond the Veterans Health Administration. This is particularly true in rheumatoid arthritis (RA), where Veteran‐centric research has uncovered novel insights into pathogenesis, risk factors, and disease manifestations, informing clinical care and research across both ...
Austin M. Wheeler, Joshua F. Baker, Jennifer L. Barton, Maria I. Danila, Tate M. Johnson, Kamini Kuchinad, Kaleb Michaud, Amir A. Razmjou, J. Steuart Richards, Namrata Singh, Isaac D. Smith, Katherine D. Wysham, Grant W. Cannon, Bryant R. England, Amy Joseph, Deana Lazaro, Katherine P. Liao, Courtney Loecker, Andreas Reimold, Beth I. Wallace, Ted R. Mikuls   +20 more
wiley   +1 more source

Momentum contrast-enhanced multimodal representation learning for drug synergy prediction. [PDF]

Bioinformatics
Gu Y, Huang X, Shi L, Chen L, Duan G, Yan C.   +5 more
europepmc   +1 more source

Automated Hand Flexor Tendon–Thickness Measurement in Systemic Sclerosis

Arthritis Care &Research, EarlyView.
Objective Systemic sclerosis (SSc) can affect flexor tendons, contributing to hand function problems and reduced quality of life. Tendon changes are currently assessed with ultrasonography and measured manually, a time‐consuming process prone to interobserver variability.
Mark Greveling, Ties van het Erve, Yvette van de Berg, Simon Mastbergen, Julia Spierings   +4 more
wiley   +1 more source

SRLST: a unified multimodal representation learning framework for spatial transcriptomics analysis. [PDF]

Bioinformatics
Lan W, Deng X, Ling T, He G, Yan X, Zheng R, Li M, Pan S, Pan Y.   +8 more
europepmc   +1 more source

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam, Anthony Siming Chen, Guido Herrmann   +2 more
wiley   +1 more source

GLUQ: Global-Local Representation Learning for UHD Image Quality Assessment. [PDF]

Entropy (Basel)
Zhu B, Chen E, Huang M, Ren X, Yu S, Sun Q.   +5 more
europepmc   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source

CPP2Vec: A representation learning approach for cell-penetrating peptides prediction. [PDF]

PLoS Comput Biol
Svolou S, Konstantakos V, Krithara A, Paliouras G.   +3 more
europepmc   +1 more source