Multi-Domain Analytics

Tensor Decomposition with ENSIGN

In this notebook, we introduce the ENSIGN Python API and demonstrate how to use tensor decomposition to analyze data.

Understanding Fake News

Show that ENSIGN can be used to learn latent variable models, or statistical models relating observed variables to unseen "hidden" variables.

COVID-19 and Workplace Closure

Study the relationship between daily COVID-19 cases and workplace closures and how it varies over space and time.

Finding "Patterns of Life" in NYC Taxi Traffic

Use ENSIGN in order to find coherent "patterns of life" in NYC taxi trip records.

Network Analysis and Anomaly Detection

Use ENSIGN to build and decompose a Bro/Zeek connections ("conn") tensor in order to gain insight into the activity occurring on a medium-sized network.

Tensor Completion for Cancer Drug Repositioning

Leverage ENSIGN's ability to find the low-rank structure of multi-dimensional data in order to propose novel drug-target-disease relationships.

Tensor Decomposition for Neural Network Compression

Leverage the natural data compression provided by tensor decomposition in order to reduce the number of parameters in a trained convolutional neural network.