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Predictive dormancy occurs when an organism enters a dormant phase before the onset of adverse conditions. For example, photoperiod and decreasing temperature are used by many plants to predict the onset of winter. Consequential dormancy occurs when organisms enter a dormant phase after adverse conditions have arisen. This is commonly found in ...
The Latent Diffusion Model (LDM) [1] is a diffusion model architecture developed by the CompVis (Computer Vision & Learning) [2] group at LMU Munich. [ 3 ] Introduced in 2015, diffusion models (DMs) are trained with the objective of removing successive applications of noise (commonly Gaussian ) on training images.
Consider, for example, how one might model the distribution of all naturally-occurring photos. Each image is a point in the space of all images, and the distribution of naturally-occurring photos is a "cloud" in space, which, by repeatedly adding noise to the images, diffuses out to the rest of the image space, until the cloud becomes all but ...
Hierarchical latent tree analysis is an alternative to LDA, which models word co-occurrence using a tree of latent variables and the states of the latent variables, which correspond to soft clusters of documents, are interpreted as topics. Animation of the topic detection process in a document-word matrix through biclustering. Every column ...
A latent space, also known as a latent feature space or embedding space, is an embedding of a set of items within a manifold in which items resembling each other are positioned closer to one another. Position within the latent space can be viewed as being defined by a set of latent variables that emerge from the resemblances from the objects.
Other latent variables correspond to abstract concepts, like categories, behavioral or mental states, or data structures. The terms hypothetical variables or hypothetical constructs may be used in these situations. The use of latent variables can serve to reduce the dimensionality of data. Many observable variables can be aggregated in a model ...
They also cast the free Direct File program as an example of the "weaponization of government against Americans," a long-standing focus of Trump and the MAGA-aligned right.
A latent variable model is a statistical model that relates a set of observable variables (also called manifest variables or indicators) [1] to a set of latent variables. Latent variable models are applied across a wide range of fields such as biology, computer science, and social science. [ 2 ]