Explanatory latent representation of heterogeneous spatial maps of ...
Explanatory latent representation of heterogeneous spatial maps of ...
We applied a data-driven approach to learn interpretable and generalizable latent representations that link cognition with underlying brain systems.
Explanatory latent representation of heterogeneous spatial maps of ...
A data-driven approach to learn interpretable and generalizable latent representations that link cognition with underlying brain systems; ...
Explanatory latent representation of heterogeneous spatial maps of ...
Explanatory latent representation of heterogeneous spatial maps of task-fMRI in large-scale datasets. M. Zabihi, S. M. Kia, T. Wolfers, S. de Boer, C. Fraza ...
Explanatory latent representation of heterogeneous spatial maps of ...
Finding an interpretable and compact representation of complex neuroimage data can be extremely useful for understanding brain behavioral mapping and hence ...
Explanatory latent representation of heterogeneous spatial maps of ...
... Explanatory latent representation of heterogeneous spatial maps of task-fMRI in large-scale datasets. Zabihi M., Kia S.M., Wolfers T., de Boer S., Fraza C ...
Mariam Zabihi - Google Scholar
Explanatory latent representation of heterogeneous spatial maps of task-fmri in large-scale datasets. M Zabihi, SM Kia, T Wolfers, S de Boer, C Fraza, S ...
charlotte fraza (0000-0002-7088-9250) - ORCID
Nonlinear latent representations of high-dimensional task-fMRI data: Unveiling cognitive and behavioral insights in heterogeneous spatial maps.
Charlotte Fraza - Google Scholar
Explanatory latent representation of heterogeneous spatial maps of task-fmri in large-scale datasets. M Zabihi, SM Kia, T Wolfers, S de Boer, C Fraza, S ...
Nonlinear latent representations of high-dimensional task-fMRI data
Nonlinear latent representations of high-dimensional task-fMRI data: Unveiling cognitive and behavioral insights in heterogeneous spatial maps. Mariam Zabihi ...
Latent Representation Learning for Geospatial Entities
In the realm of spatial data, representation learning has played a crucial role in extracting latent patterns within various data types, such as ...
Stijn de Boer (0000-0002-8657-8959) - ORCID
Explanatory latent representation of heterogeneous spatial maps of task-fMRI in large-scale datasets ... Contributors: Mariam Zabihi; Seyed Mostafa Kia; Thomas ...
Sourena Soheili-Nezhad - Google Scholar
Explanatory latent representation of heterogeneous spatial maps of task-fmri in large-scale datasets. M Zabihi, SM Kia, T Wolfers, S de Boer, C Fraza, S ...
Deep generative priors for biomolecular 3D heterogeneous ...
... latent encoding. Ideally, each dimension of the representation in the latent space could indicate independent variation in conformational heterogeneity. The ...
[PDF] Formal Models of the Network Co-occurrence Underlying ...
... model-based generation of synthetic activity maps ... Explanatory latent representation of heterogeneous spatial maps of task-fMRI in large-scale datasets.
Spatial heterogeneity automatic detection and estimation
Abstract. Spatial regression is widely used for modeling the relationship between a dependent variable and explanatory covariates. Oftentimes, the linear ...
Nonlinear latent representations of high-dimensional task-fMRI data
Nonlinear latent representations of high-dimensional task-fMRI data: Unveiling cognitive and behavioral insights in heterogeneous spatial maps.
Spatially explicit predictions using spatial eigenvector maps - Guénard
... explanatory descriptors. That property entails that pMEM is a method ... spatial coordinates in the model, in the form of latent variables.
Representation learning on heterogeneous spatiotemporal networks
The problem of learning latent representations of heterogeneous networks with spatial and temporal attributes has been gaining traction in ...
(PDF) Latent feature sharing: an adaptive approach to linear ...
Explanatory latent representation of heterogeneous spatial maps of task-fMRI in large-scale datasets · Stijn de Boer. 2021. Finding an interpretable and compact ...
Machine learning in resting-state fMRI analysis - ar5iv - arXiv
The primary objective of unsupervised learning is to discover latent representations and disentangle the explanatory ... spatial maps from group level latent maps ...