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  2. Latent diffusion model - Wikipedia

    en.wikipedia.org/wiki/Latent_Diffusion_Model

    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.

  3. List of phylogenetic tree visualization software - Wikipedia

    en.wikipedia.org/wiki/List_of_phylogenetic_tree...

    an online tool for phylogenetic tree view (newick format) that allows multiple sequence alignments to be shown together with the trees (fasta format) EvolView [3] an online tool for visualizing, annotating and managing phylogenetic trees IcyTree [4] Client-side Javascript SVG viewer for annotated rooted trees. Also supports phylogenetic networks

  4. Behavior tree (artificial intelligence, robotics and control)

    en.wikipedia.org/wiki/Behavior_tree_(artificial...

    Behavior trees became popular for their development paradigm: being able to create a complex behavior by only programming the NPC's actions and then designing a tree structure (usually through drag and drop) whose leaf nodes are actions and whose inner nodes determine the NPC's decision making. Behavior trees are visually intuitive and easy to ...

  5. Stable Diffusion - Wikipedia

    en.wikipedia.org/wiki/Stable_Diffusion

    Stable Diffusion originated from a project called Latent Diffusion, [11] developed in Germany by researchers at Ludwig Maximilian University in Munich and Heidelberg University. Four of the original 5 authors (Robin Rombach, Andreas Blattmann, Patrick Esser and Dominik Lorenz) later joined Stability AI and released subsequent versions of Stable ...

  6. Latent and observable variables - Wikipedia

    en.wikipedia.org/wiki/Latent_and_observable...

    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 ...

  7. Latent Dirichlet allocation - Wikipedia

    en.wikipedia.org/wiki/Latent_Dirichlet_allocation

    In natural language processing, latent Dirichlet allocation (LDA) is a Bayesian network (and, therefore, a generative statistical model) for modeling automatically extracted topics in textual corpora. The LDA is an example of a Bayesian topic model. In this, observations (e.g., words) are collected into documents, and each word's presence is ...

  8. LAMP (software bundle) - Wikipedia

    en.wikipedia.org/wiki/LAMP_(software_bundle)

    Linux is a Unix-like computer operating system assembled under the model of free and open-source software development and distribution. Most Linux distributions , as collections of software based around the Linux kernel and often around a package management system , provide complete LAMP setups through their packages.

  9. Tree (abstract data type) - Wikipedia

    en.wikipedia.org/wiki/Tree_(abstract_data_type)

    Trees are commonly used to represent or manipulate hierarchical data in applications such as: . File systems for: . Directory structure used to organize subdirectories and files (symbolic links create non-tree graphs, as do multiple hard links to the same file or directory)