NorskRegnesentral/IQD

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R
Created almost 5 years ago
Updated 7 months ago

NorskRegnesentral/IQD

NorskRegnesentral

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Functions to calculate the integrated qudratic distance (IQD)

skweak

skweak: A software toolkit for weak supervision applied to NLP tasks

shapr

Explaining the output of machine learning models with more accurately estimated Shapley values

weak-supervision-for-NER

Framework to learn Named Entity Recognition models without labelled data using weak supervision.

Jupyter Notebook

text-anonymization-benchmark

Annotated corpus + evaluation metrics for text anonymisation

NeuralTextSanitizer

Neural models for detecting and masking personal information from texts

skchange

skchange provides sktime-compatible change detection and changepoint-based anomaly detection algorithms

streamchange

A package for segmenting streaming time series data into homogenous segments. The segmentation is based on statistical change-point detection (aka online/sequential/iterative change-point detection).

mccepy

Python package to generate counterfactuals using Monte Carlo sampling of realistic counterfactual explanations

smms

R package for fitting semi-markovian multistate models

explego

eXplego is a decision tree toolkit that provides developers with interactive guidance to help select an appropriate XAI-method for their particular use case.

SpatGEVBMA

R-package fitting a Bayesian hierarchical spatial model for the generalized extreme value distribution with the option of model averaging over the space of covariates

nrresqml

Python package for converting Delft3D models (netcdf) to ResQml

mcceR

naturinngrep

vargrest

Variogram estimation for ResQml models (related to nrresqml)

NRTools

Tools used by Alex Lenkoski at the Norwegian Computing Center to develop R packages

channest

Channel parameter estimation for ResQml models (related to nrresqml)

spatioTemporalIndices

GraphDial

Python framework for graph-based dialogue management

IVBMA

ai4artic_snow

Estimation of snow-parameters from sentinel-3 data using deep learning