Results 91 to 100 of about 24,544,958 (149)

AI-Driven multi-view learning from CCTA for myocardial infarction diagnosis. [PDF]

Int J Cardiovasc Imaging
Gwizdala J, Salihu A, Senouf O, Meier D, Rotzinger D, Qanadli S, Muller O, Frossard P, Abbe E, Thanou D, Fournier S, Auberson D.   +11 more
europepmc   +1 more source

MVRBind: multi-view learning for RNA-small molecule binding site prediction. [PDF]

Brief Bioinform
Chen S, Huang Z, Wang Y, Li Y, Tan YS, Deng L, Wu M.   +6 more
europepmc   +1 more source

TSCMamba: Mamba Meets Multi-View Learning for Time Series Classification. [PDF]

Inf Fusion
Ahamed MA, Cheng Q.
europepmc   +1 more source

DNN-MVL: DNN-Multi-View-Learning-Based Recover Block Missing Data in a Dam Safety Monitoring System. [PDF]

Sensors (Basel), 2019
Mao Y, Zhang J, Qi H, Wang L.
europepmc   +1 more source

NMFGOT: a multi-view learning framework for the microbiome and metabolome integrative analysis with optimal transport plan. [PDF]

NPJ Biofilms Microbiomes
Ma Y, Liu L.
europepmc   +1 more source

A multi-view learning approach with diffusion model to synthesize FDG PET from MRI T1WI for diagnosis of Alzheimer's disease. [PDF]

Alzheimers Dement
Chen K, Weng Y, Huang Y, Zhang Y, Dening T, Hosseini AA, Xiao W.   +6 more
europepmc   +1 more source

Semi-Supervised Multi-View Learning for Gene Network Reconstruction. [PDF]

PLoS One, 2015
Ceci M, Pio G, Kuzmanovski V, Džeroski S.   +3 more
europepmc   +1 more source

Adaptive multi-view learning method for enhanced drug repurposing using chemical-induced transcriptional profiles, knowledge graphs, and large language models. [PDF]

J Pharm Anal
Yan Y, Yang Y, Tong Z, Wang Y, Yang F, Pan Z, Liu C, Bai M, Xie Y, Li Y, Shu K, Li Y.   +11 more
europepmc   +1 more source

Multi-view learning framework for predicting unknown types of cancer markers via directed graph neural networks fitting regulatory networks. [PDF]

Brief Bioinform
Wang XF, Huang L, Wang Y, Guan RC, You ZH, Sheng N, Xie XP, Hou WJ.   +7 more
europepmc   +1 more source

ViewFusion: Learning Composable Diffusion Models for Novel View Synthesis

Publisher Copyright: © 2025, Transactions on Machine Learning Research. All rights reserved.Deep learning is providing a wealth of new approaches to the problem of novel view synthesis, from Neural Radiance Field (NeRF) based approaches to end-to-end ...
Spiegl, Bernard, Deny, Stéphane, Perin, Andrea, Ilin, Alexander   +3 more
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