Reproduces the results of MinCutPool as presented in the 2020 ICML paper "Spectral Clustering with Graph Neural Networks for Graph Pooling".

A wiki containing information about NEU's Discovery Cluster.

Unsupervised classification of the North Eastern University Steel Surface Defects Database

Implementation of "Just Balance GNN" for graph classification and node clustering from the paper "Simplifying Clusterings with Graph Neural Networks".

Implementation of the Neural Clustering Process algorithm in Pytorch

Deep Learning Clustering with Tensor-Flow in Python

Autoencoders - a deep neural network was used for feature extraction followed by clustering of the "Cancer" dataset using k-means technique

Code for the paper "XAI Beyond Classification: Interpretable Neural Clustering" (JMLR 2022)

Code for 'Unbiased Monte Carlo Cluster Updates with Autoregressive Neural Networks'.

No description available

Implementation of Graph pooling and clustering operation using Graph Neural Networks in PyTorch

Hello World examples running on the NEU Discovery Cluster.

Implementation for the paper Neural Survival Clustering: Non parametric mixture of neural networks for survival clustering

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Unsupervised clustering of patients using CNN with Deep Learning

Fuzzy Clustering Using Hybrid Fuzzy c-means and Fuzzy Particle Swarm Optimization (A Research Paper Implementation along with Self-organization feature map (SOFM) implementation)

Setup for doing neuroimaging on the cluster.

Implementation of "Identifying treatment response subgroups in observational time-to-event data" Jeanselme et al.

Python pipeline for non-parametric cluster-based permutation testing for electrophysiological signals related to complex behaviors.

Neuronal Cluster Analysis for scRNA-Seq data (mouse brain)

No description available

Neural Clustering project - Machine Learning with Probabilistic Programming @ Columbia

A simple multilayer cluster neural network trained with the back propagation algorithm

Neural Networks project including SOM clustering/classification and SLFN implementation from scratch.

This program uses Self Organizing maps for text mining purposes.

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Examples of how to invoke dask/scoop for embarrassingly parallel jobs on NEU's discovery cluster

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Clustering with neural networks can be applied to: * Image feature clustering (e.g. face grouping) * Customer segmentation * Document/topic modeling * Any unsupervised representation learning task

Deep Learning Clustering with Tensor-Flow in Python