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  2. Latent diffusion model - Wikipedia

    en.wikipedia.org/wiki/Latent_Diffusion_Model

    The encoder part of the VAE takes an image as input and outputs a lower-dimensional latent representation of the image. This latent representation is then used as input to the U-Net. Once the model is trained, the encoder is used to encode images into latent representations, and the decoder is used to decode latent representations back into images.

  3. Convolutional code - Wikipedia

    en.wikipedia.org/wiki/Convolutional_code

    To convolutionally encode data, start with k memory registers, each holding one input bit.Unless otherwise specified, all memory registers start with a value of 0. The encoder has n modulo-2 adders (a modulo 2 adder can be implemented with a single Boolean XOR gate, where the logic is: 0+0 = 0, 0+1 = 1, 1+0 = 1, 1+1 = 0), and n generator polynomials — one for each adder (see figure below).

  4. BERT (language model) - Wikipedia

    en.wikipedia.org/wiki/BERT_(language_model)

    High-level schematic diagram of BERT. It takes in a text, tokenizes it into a sequence of tokens, add in optional special tokens, and apply a Transformer encoder. The hidden states of the last layer can then be used as contextual word embeddings. BERT is an "encoder-only" transformer architecture. At a high level, BERT consists of 4 modules:

  5. Code-excited linear prediction - Wikipedia

    en.wikipedia.org/wiki/Code-excited_linear_prediction

    Code-excited linear prediction (CELP) is a linear predictive speech coding algorithm originally proposed by Manfred R. Schroeder and Bishnu S. Atal in 1985. At the time, it provided significantly better quality than existing low bit-rate algorithms, such as residual-excited linear prediction (RELP) and linear predictive coding (LPC) vocoders (e.g., FS-1015).

  6. Stable Diffusion - Wikipedia

    en.wikipedia.org/wiki/Stable_Diffusion

    Diagram of the latent diffusion architecture used by Stable Diffusion The denoising process used by Stable Diffusion. The model generates images by iteratively denoising random noise until a configured number of steps have been reached, guided by the CLIP text encoder pretrained on concepts along with the attention mechanism, resulting in the ...

  7. List of Unified Modeling Language tools - Wikipedia

    en.wikipedia.org/wiki/List_of_Unified_Modeling...

    Supports following UML diagrams: Use case diagram, Sequence diagram, Collaboration diagram, Class diagram, Statechart diagram, Activity diagram, Component diagram, Deployment diagram and Package diagram Rational Rose XDE: No Un­known Un­known Un­known Un­known Un­known Un­known Rational Software Architect: Yes Yes Yes Un­known

  8. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    List of GitHub repositories of the project: Kubernetes SIGs This data is not pre-processed List of GitHub repositories of the project: Konveyor This data is not pre-processed List of GitHub repositories of the project: RedHat Marketplace This data is not pre-processed List of GitHub repositories of the project: Redhat blog This data is not pre ...

  9. Priority encoder - Wikipedia

    en.wikipedia.org/wiki/Priority_encoder

    Applications of priority encoders include their use in interrupt controllers (to allow some interrupt requests to have higher priority than others), decimal or binary encoding, and analog-to-digital / digital to-analog conversion. [2] Gate-level diagram of a single bit 4-to-2 priority encoder. I(3) has the highest priority.