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6 results for “Latent Variable Models”
BioVAE: a pre-trained latent variable language model for biomedical text mining
<p>We release BioVAE, the first large-scale pre-trained latent variable language model for the biomedical domain, which uses the OPTIMUS framework to train on large volumes of biomedical text.</p> <p>This version contains the pre-trained models for text mining tasks such as named entity recognition or relation extraction, and text generation task.</p> <p>Explanation of each file: (lt32: latent_size = 32, beta05: beta=0.5)</p> <ul> <li>pm-full-lt32-beta00</li> <li>pm-full-lt32-beta05</li> <li>pm-full-lt768-beta00</li> <li>pm-full-lt768-beta05</li> <li>pm-full-generation</li> </ul>
Supplementary material 1 from: Grace JB, Steiner M (2021) A protocol for modelling generalised biological responses using latent variables in structural equation models. One Ecosystem 6: e67320. https://doi.org/10.3897/oneeco.6.e67320
A protocol for modelling generalised biological responses using latent variables in structural equation models
Supplementary material 3 from: Grace JB, Steiner M (2021) A protocol for modelling generalised biological responses using latent variables in structural equation models. One Ecosystem 6: e67320. https://doi.org/10.3897/oneeco.6.e67320
A protocol for modelling generalised biological responses using latent variables in structural equation models
Supplementary material 2 from: Grace JB, Steiner M (2021) A protocol for modelling generalised biological responses using latent variables in structural equation models. One Ecosystem 6: e67320. https://doi.org/10.3897/oneeco.6.e67320
A protocol for modelling generalised biological responses using latent variables in structural equation models
Skabbholmen data from: Concurrent ordination: Simultaneous unconstrained and constrained latent variable modeling
<ol> <li>In community ecology, unconstrained ordination can be used to indirectly explore drivers of community composition, while constrained ordination can be used to directly relate predictors to an ecological community. However, existing constrained ordination methods do not explicitly account for community composition that cannot be explained by the predictors, so that they have the potential to misrepresent community composition if not all predictors are available in the data.</li> <li>We propose and develop a set of new methods for ordination and Joint Species Distribution Modelling (JSDM) as part of the Generalized Linear Latent Variable Model (GLLVM) framework, that incorporate predictors directly into an ordination. This includes a new ordination method that we refer to as concurrent ordination, as it simultaneously constructs unconstrained and constrained latent variables. Both unmeasured residual covariation and predictors are incorporated into the ordination by simultaneously imposing reduced rank structures on the residual covariance matrix and on fixed-effects.</li> <li>We evaluate the method with a simulation study, and show that the proposed developments outperform Canonical Correspondence Analysis (CCA) for Poisson and Bernoulli responses, and perform similar to Redundancy Analysis (RDA) for normally distributed responses, the two most popular methods for constrained ordination in community ecology. Two examples with real data further demonstrate the benefits of concurrent ordination, and the need to account for residual covariation in the analysis of multivariate data.</li> <li>This article contextualizes the role of constrained ordination in the GLLVM and JSDM frameworks, while developing a new ordination method that incorporates the best of unconstrained and constrained ordination, and which overcomes some of the deficiencies of existing classical ordination methods.</li> </ol>
Skabbholmen data from: Concurrent ordination: Simultaneous unconstrained and constrained latent variable modeling
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.