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  2. Normalization (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Normalization_(machine...

    Weight normalization (WeightNorm) [18] is a technique inspired by BatchNorm that normalizes weight matrices in a neural network, rather than its activations. One example is spectral normalization , which divides weight matrices by their spectral norm .

  3. List of mass spectrometry software - Wikipedia

    en.wikipedia.org/wiki/List_of_mass_spectrometry...

    It supports DIA-based profiling of PTMs, such as phosphorylation and ubiquitination, new technologies such as Scanning SWATH [36] and dia-PASEF, [37] and can perform library-free analyses (acts as a database search engine). [38] FlashLFQ Open source: FlashLFQ is an ultrafast label-free quantification algorithm for mass-spectrometry proteomics. [39]

  4. Batch normalization - Wikipedia

    en.wikipedia.org/wiki/Batch_normalization

    In a neural network, batch normalization is achieved through a normalization step that fixes the means and variances of each layer's inputs. Ideally, the normalization would be conducted over the entire training set, but to use this step jointly with stochastic optimization methods, it is impractical to use the global information.

  5. Flow-based generative model - Wikipedia

    en.wikipedia.org/wiki/Flow-based_generative_model

    A flow-based generative model is a generative model used in machine learning that explicitly models a probability distribution by leveraging normalizing flow, [1] [2] [3] which is a statistical method using the change-of-variable law of probabilities to transform a simple distribution into a complex one.

  6. Vanishing gradient problem - Wikipedia

    en.wikipedia.org/wiki/Vanishing_gradient_problem

    Weight initialization [ edit ] Kumar suggested that the distribution of initial weights should vary according to activation function used and proposed to initialize the weights in networks with the logistic activation function using a Gaussian distribution with a zero mean and a standard deviation of 3.6/sqrt(N) , where N is the number of ...

  7. Atmospheric Rivers Could Become Stronger, Study Suggests - AOL

    www.aol.com/news/atmospheric-rivers-could-become...

    The amount of water they move is mindblowing – a strong atmospheric river can transport as much water vapor as up to 15 times the average flow of liquid water at the mouth of the Mississippi River.

  8. Feature scaling - Wikipedia

    en.wikipedia.org/wiki/Feature_scaling

    Without normalization, the clusters were arranged along the x-axis, since it is the axis with most of variation. After normalization, the clusters are recovered as expected. In machine learning, we can handle various types of data, e.g. audio signals and pixel values for image data, and this data can include multiple dimensions. Feature ...

  9. 11 must-see astronomy events in 2025 - AOL

    www.aol.com/11-must-see-astronomy-events...

    Stargazers should prepare to lose sleep on Tuesday, Aug. 12, as two celestial sights unfold. The first event will be visible before sunrise and will feature the two brightest planets in the sky ...