Statistical Machine Intelligence & Learning Engine
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Updated
Jun 1, 2024 - Java
Statistical Machine Intelligence & Learning Engine
🔴 MiniSom is a minimalistic implementation of the Self Organizing Maps
PHATE (Potential of Heat-diffusion for Affinity-based Transition Embedding) is a tool for visualizing high dimensional data.
Pytorch implementation of Hyperspherical Variational Auto-Encoders
Single cell trajectory detection
Tensorflow implementation of Hyperspherical Variational Auto-Encoders
CellRank: dynamics from multi-view single-cell data
Data Science and Matrix Optimization course
Introduction to Manifold Learning - Mathematical Theory and Applied Python Examples (Multidimensional Scaling, Isomap, Locally Linear Embedding, Spectral Embedding/Laplacian Eigenmaps)
Manifold-learning flows (ℳ-flows)
Tensorflow implementation of adversarial auto-encoder for MNIST
A Julia package for manifold learning and nonlinear dimensionality reduction
A Framework for Dimensionality Reduction in R
An example project that predicts risk of credit card default using a Logistic Regression classifier and a 30,000 sample dataset.
Dimension Reduction and Estimation Methods
This is the code implementation for the GMML algorithm.
Pytorch code for “Unsupervised Domain Adaptation via Discriminative Manifold Embedding and Alignment ” (DRMEA) (AAAI 2020).
This will show how to make autoencoders using pytorch neural networks
Geometry Regularized Autoencoders (GRAE) for large-scale visualization and manifold learning
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