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A bivariate, multimodal distribution Figure 4. A non-example: a unimodal distribution, that would become multimodal if conditioned on either x or y. In statistics, a multimodal distribution is a probability distribution with more than one mode (i.e., more than one local peak of the distribution).
If it has more modes it is "bimodal" (2), "trimodal" (3), etc., or in general, "multimodal". [2] Figure 1 illustrates normal distributions, which are unimodal. Other examples of unimodal distributions include Cauchy distribution, Student's t-distribution, chi-squared distribution and exponential distribution.
Such channels may differ based on sensory nature (e.g., visual vs. auditory), [1] or other significant differences in processing (e.g., text vs. image). [2] A system is designated unimodal if it has only one modality implemented, and multimodal if it has more than one. [1]
Such a continuous distribution is called multimodal (as opposed to unimodal). In symmetric unimodal distributions, such as the normal distribution, the mean (if defined), median and mode all coincide. For samples, if it is known that they are drawn from a symmetric unimodal distribution, the sample mean can be used as an estimate of the ...
Multimodal learning, machine learning methods using multiple input modalities; Multimodal transport, a contract for delivery involving the use of multiple modes of goods transport; Multimodality, the use of several modes (media) in a single artifact; Multimodal logic modal logic that has more than one primitive modal operator
Unimodal association cortex: This area receives input from a single sensory modality. The output from the unimodal cortex is largely to unimodal areas. For example, the visual association cortex in the occipital lobe processes visual information, and the auditory association cortex in the temporal lobe processes auditory information.
Multimodal learning is a type of deep learning that integrates and processes multiple types of data, referred to as modalities, such as text, audio, images, or video.This integration allows for a more holistic understanding of complex data, improving model performance in tasks like visual question answering, cross-modal retrieval, [1] text-to-image generation, [2] aesthetic ranking, [3] and ...
A modal logic with n primitive unary modal operators , {, …,} is called an n-modal logic.Given these operators and negation, one can always add modal operators defined as if and only if , to give a classical multimodal logic if it is in addition stable under necessitation (or "possibilization", therefore) of both members of provable equivalences.