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pychange

Multiple change detection with python

recombat

reComBat package to correct batch effects

ripser

Ripser: efficient computation of Vietoris–Rips persistence barcodes

s3m

A software package for statistically significant shapelet mining

sampling-outlier-detection

Rapid computation of distance-based outlierness scores via sampling

sapiens

sat

Official Pytorch code for Structure-Aware Transformer.

sc-autoencoding

student internship of Simon Streib to reduce single cell data

scikit-learn

scikit-learn: machine learning in Python

scirecoverypredictionpublic

We provide a simple matching algorithm to identify digital twins for spinal cord injury patients in the acute injury phase.

scones

Selecting CONected Explanatory SNPs

sepsis-prediction-review

set_functions_for_time_series

Repository of the ICML 2020 paper "Set Functions for Time Series"

shap

A game theoretic approach to explain the output of any machine learning model.

significant-pattern-mining-with-covariates-facs

Fast Automatic Conditional Search in the presence of categorical covariates (Papaxanthos et al., NIPS 2016) http://goo.gl/dNmZE4

significant-pattern-mining-wylight

significant-subgraph-mining

Finding statistically significant subgraphs while correcting for multiple testing

simbsig

The official implementation for the SIMBSIG package

sinimin

Significant Network Interval Mining

spss

Code for pediatric sepsis study

tda-cnn-ad

Model combining topological descriptors with patch based MR imaging features

togl

Topological Graph Neural Networks (ICLR 2022)

topf

Topological peak filtering

topo-ae-distances

topological-autoencoders

Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.

uea_ucr_datasets

A small package for loading and handling UEA UCR time series classification datasets.

wtk

A Wasserstein Subsequence Kernel for Time Series.

wwl

Wasserstein Weisfeiler-Lehman Graph Kernels