predict-idlab/sleep-linear

Stars
35
Rank 729,537 (Top 15 %)
Language
Jupyter Notebook
License
Other
Created almost 2 years ago
Updated 6 months ago

predict-idlab/sleep-linear

predict-idlab

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Do not sleep on traditional machine learning for sleep stage scoring

plotly-resampler

Visualize large time series data with plotly.py

tsflex

Flexible time series feature extraction & processing

powershap

A power-full Shapley feature selection method.

tsdownsample

High-performance time series downsampling algorithms for visualization

Jupyter Notebook

RR-GCN

Code for "R-GCN: The R Could Stand for Random"

seriesdistancematrix

ts-datapoint-selection-vis

Data Point Selection for Line Chart Visualization: analysis notebooks and implementation details

trace-updater

Dash component to update a dcc.Graph its traces via callbacks

MinMaxLTTB

MinMax-preselection for Efficient Time Series Line Chart Visualization (using LTTB)

causalteshap

Jupyter Notebook

tsflex-benchmarking

VisCARS

VisCARS: Graph-Based Context-Aware Visualization Recommendation System

Jupyter Notebook

cmc-learner

Implementation of Conformal Monte Carlo (CMC) learner

Jupyter Notebook

class-balancing-paper

Jupyter Notebook

The-Distribution-Coverage-Loss

Jupyter Notebook

ddashboard-ontology

Ontology for the Dynamic Dashboard

REACT

Jupyter Notebook

landmarker

PyTorch-based toolkit for landmark detection

svd-kernels

Repository for code regarding the paper "Parameter-efficient neural networks with singular value decomposed kernels"

Jupyter Notebook

gssp_analysis

Analysis notebooks and scripts of the gssp web app data collection

Jupyter Notebook

DAHCC-Sources

Resource files for all ontologies described at https://dahcc.idlab.ugent.be

gssp_web_app

Web application to acquire picture description speech data according to the GSSP

plotly-resampler-benchmarks

Jupyter Notebook

obelisk-python

Python client for the Obelisk API

data-quality-challenges-wearables

Addressing Data Quality Challenges in Observational Ambulatory Studies: Analysis, methodologies and practical solutions for wrist-worn wearable monitoring

Jupyter Notebook

webthing-client-python

Python client for Dynamic Dashboard Webthings

atrial_fibrillation_prediction

Jupyter Notebook

phys-ml-leak-localization

Jupyter Notebook