michaelwozniak

michaelwozniak's Stars

• Keytoyze/VisionTS

  Code for our paper "VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters".

  Language:Jupyter Notebook873

• sktime/skpro

  A unified framework for tabular probabilistic regression and probability distributions in python

  Language:Python23245

• scikit-learn-contrib/skglm

  Fast and modular sklearn replacement for generalized linear models

  Language:Python15629

• moment-timeseries-foundation-model/moment

  MOMENT: A Family of Open Time-series Foundation Models

  Language:TypeScript30351

• NX-AI/xlstm

  Official repository of the xLSTM.

  Language:Python1.2k88

• ibm-granite/granite-tsfm

  Foundation Models for Time Series

  Language:Jupyter Notebook337165

• rsteca/sklearn-deap

  Use evolutionary algorithms instead of gridsearch in scikit-learn

  Language:Jupyter Notebook772131

• gmgeorg/pylambertw

  pylambertw - sklearn interface to analyze and gaussianize heavy-tailed, skewed data

  Language:Jupyter Notebook91

• linkedin/luminol

  Anomaly Detection and Correlation library

  Language:Python1.2k215

• astrogilda/tsbootstrap

  tsbootstrap: generate bootstrapped time series samples in Python

  Language:Python685

• amazon-science/chronos-forecasting

  Chronos: Pretrained (Language) Models for Probabilistic Time Series Forecasting

  Language:Python2.3k266

• s-marton/GRANDE

  (ICLR 2024) GRANDE: Gradient-Based Decision Tree Ensembles

  Language:Jupyter Notebook848

• Blue-Yonder-OSS/cyclic-boosting

  implementation of Cyclic Boosting machine learning algorithms

  Language:Python8715

• michaelwozniak/trendecon

  Create Long Daily Series from Google Trends

  1

• ml-jku/HopCPT

  Conformal Prediction for Time Series with Modern Hopfield Networks

  Language:Python677

• KulikDM/pythresh

  Outlier Detection Thresholding

  Language:Jupyter Notebook1235

• bashtage/arch

  ARCH models in Python

  Language:Python1.3k246

• cerlymarco/tspiral

  A python package for time series forecasting with scikit-learn estimators.

  Language:Jupyter Notebook15819

• PingChang818/TDSTF

  Language:Python6011

• mims-harvard/TFC-pretraining

  Self-supervised contrastive learning for time series via time-frequency consistency

  Language:Python42278

• GBDT-PL/GBDT-PL

  Gradient Boosting With Piece-Wise Linear Trees

  Language:C++14726

• LongxingTan/Time-series-prediction

  tfts: Time Series Deep Learning Models in TensorFlow

  Language:Python814163

• mckinsey/causalnex

  A Python library that helps data scientists to infer causation rather than observing correlation.

  Language:Python2.2k256

• Nixtla/nixtla

  TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.

  Language:Jupyter Notebook2.2k172

• Nixtla/neuralforecast

  Scalable and user friendly neural :brain: forecasting algorithms.

  Language:Python2.9k336

• predict-idlab/powershap

  A power-full Shapley feature selection method.

  Language:Python19318

• AutoViML/Auto_TS

  Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Created by Ram Seshadri. Collaborators welcome.

  Language:Jupyter Notebook722113

• uncertainty-toolbox/uncertainty-toolbox

  Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization

  Language:Python1.8k129

• henrikbostrom/crepes

  Conformal classifiers, regressors and predictive systems

  Language:Python42433

• StatMixedML/LightGBMLSS

  An extension of LightGBM to probabilistic modelling

  Language:Python26525