MS-Mapping: An Uncertainty-Aware Large-Scale Multi-Session LiDAR Mapping System
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Updated
Jul 11, 2024
MS-Mapping: An Uncertainty-Aware Large-Scale Multi-Session LiDAR Mapping System
Pytorch implementation of same-family gaussian mixture models with guardrails. Features separable parameter optimization and singularity mitigation
Additional linear models including instrumental variable and panel data models that are missing from statsmodels.
This repository is the official implementation of Disentangling Writer and Character Styles for Handwriting Generation (CVPR23).
Code release for "An open-source robust machine learning platform for real-time detection and classification of 2D material flakes"
package for Bayesian and classical estimation and inference based on statistics that are filtered through a trained neural net
A LibreOffice Calc extension that clusters the rows in a table and colors them to indicate the clusters.
Gaussian mixture models, k-means, mini-batch-kmeans and k-medoids clustering
A web API and portal to explote, select and test Ground Shaking Intensity Models
This project looks to investigate if there is a connection between clusters of ocean temperature in the southern hemisphere and the properties of the Southern Annular Mode (SAM)
Intelligent monitoring of escalator.Function including traffic statistics,passenger retention detection and large object retention detection in escalator floor board. As well as human keypoints extraction and tracking in elevator.
Implementation of Expectation-Maximization (EM) algorithm for Gaussian Mixture Model
A collection of clustering algorithms implemented in Python and C++, complete with a GUI for simulation and educational purposes, showcasing data analysis techniques." This description succinctly outlines the purpose and contents of the repository within the constraints provided.
Implementation of Task-Parameterized-Gaussian-Mixture-Models as presented from S. Calinon in his paper: "A Tutorial on Task-Parameterized Movement Learning and Retrieval"
Regression, Classification, Clustering, Dimension-reduction, Anomaly detection
codes to cluster stocks into groups based on value at risk using K-Means, Agglomerative, and GMM.
Code and data associated with the paper "Superiority of quadratic over conventional neural networks for classification of Gaussian mixture data."
TexnoMagic library for digital Magic
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