Self-Supervised Noise Embeddings (Self-SNE)
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Updated
Jun 6, 2024 - Jupyter Notebook
Self-Supervised Noise Embeddings (Self-SNE)
FeatureMAP (Feature-preserving Manifold Approximation and Projection) is an interpratable dimensionality reduction tool.
An R package for detecting cell-to-cell variably methylated regions (VMRs) from single-cell bisulfite sequencing.
Clustering skin diseases using DINOv2 embeddings.
Increase processing efficiency via principal components analysis
A Julia package for multivariate statistics and data analysis (e.g. dimension reduction)
This repository contains a project for customer segmentation using the K-Means clustering algorithm. The goal is to group customers into distinct clusters based on their demographic and purchasing behavior to better understand customer segments and target them effectively.
JavaScript implementation of UMAP
Project to demonstrate various clustering algorithms for customer segmentation.
Mutual Information-based Non-linear Clustering Analysis
IU Projects
Manifold Learning via Diffusion Maps in Julia
Applying statistical data science methods into loan default prediction task
TorchDR - PyTorch Dimensionality Reduction
📊VIDAR: Visualization Interface for Data Analytics and Reduction
"Welcome to my GitHub repository! Here, you'll find a hub of projects and code dedicated to the fascinating world of statistical analytics. From crunching numbers to extracting meaningful insights, join me on a journey through the realm of data-driven decision-making. Let's explore the power of statistics together!"
A Python library for the fast symbolic approximation of time series
Single cell trajectory detection
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