Statistical Machine Intelligence & Learning Engine
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Updated
May 21, 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.
This will show how to make autoencoders using pytorch neural networks
Pytorch code for “Unsupervised Domain Adaptation via Discriminative Manifold Embedding and Alignment ” (DRMEA) (AAAI 2020).
A set of notebooks as a guide to the process of fine-grained image classification of birds species, using PyTorch based deep neural networks.
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