Showing 5 open source projects for "mixture"

View related business solutions
  • MongoDB Atlas runs apps anywhere Icon
    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

    MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
    Start Free
  • Go From AI Idea to AI App Fast Icon
    Go From AI Idea to AI App Fast

    One platform to build, fine-tune, and deploy ML models. No MLOps team required.

    Access Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
    Try Free
  • 1
    SMTracker (v1.5, v2.0)

    SMTracker (v1.5, v2.0)

    A tool for analysis and visualization of single-molecule tracking data

    SMTracker v2.0 is a MATLAB-based graphical user interface (GUI) for automatically quantifying, visualising and managing SMT data via five interactive panels, allowing the user to interactively explore tracking data from several conditions, movies and cells on a track-by- track basis. Diffusion parameters and motion behaviour is analysed by several methods: a) by a Gaussian mixture model ,or b) by using the cumulative probability distribution of square displacements, c) Mean-Squared displacement fits, d) by Jump Distance analysis. It also includes exploratory tools to visualise single trajectories or dynamic heat maps.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2

    fitGCP

    Fitting genome coverage distributions with mixture models

    ...fitGCP is a framework for fitting mixtures of probability distributions to genome coverage profiles. Besides commonly used distributions, fitGCP uses distributions tailored to account for common artifacts. The mixture models are iteratively fitted based on the Expectation-Maximization algorithm. Please find the accompanying paper here: http://dx.doi.org/10.1093/bioinformatics/btt147
    Downloads: 0 This Week
    Last Update:
    See Project
  • 3

    BiomeNet

    BAYESIAN INFERENCE OF METABOLIC DIVERGENCE AMONG MICROBIAL COMMUNITIES

    ...To infer the structure of community-level metabolic interactions, BiomeNet applies a mixed-membership modelling framework to enzyme abundance information. The basic idea is that the mixture components of the model (metabolic reactions, subnetworks, and networks) are shared across all groups (microbiome samples), but the mixture proportions vary from group to group. Through this framework, the model can capture nested structures within the data. BiomeNet is unique in modeling each metagenome sample as a mixture of complex metabolic systems (metabosystems).
    Downloads: 0 This Week
    Last Update:
    See Project
  • 4

    MCTIMME

    Microbial Counts Trajectories Infinite Mixture Model Engine

    MCTIMME is a nonparametric Bayesian computational framework for analyzing microbial time-series data.The current implementation is in Matlab.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Forever Free Full-Stack Observability | Grafana Cloud Icon
    Forever Free Full-Stack Observability | Grafana Cloud

    Our generous forever free tier includes the full platform, including the AI Assistant, for 3 users with 10k metrics, 50GB logs, and 50GB traces.

    Built on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
    Create free account
  • 5
    A straight-forward Java implementation of a mixture model with pluggable mixture functions, e.g. a mixture of Gaussian functions. The number and dimensionality of the mixture functions is not limited. All critical calculations are performed in log-space.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next