Vitor Cerqueira

experiments-sizematters. Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters

experiments-performance_estimation. Comparing different performance estimation methods for time series forecasting tasks

tsensembler. R package - Dynamic Ensembles for Time Series Forecasting

tsa4climate. Tackling Climate Change with Time Series Analysis and Forecasting

experiments-vest. Lag-based feature extraction for forecasting

medium-articles. Jupyter Notebook

deprecated-vest. Automatic Feature Engineering for Time Series

experiments-studd. Experiments with label-free concept drift detection

experiments-icll. Layered Learning for Imbalanced Classification

experiments-multioutput_ensembles. Multi-output Ensembles for Multi-step Forecasting

metaforecast. Meta-learning and Data-centric Time Series Forecasting

networksampling. Sampling Large Scale Networks with Metropolis-Hastings Random Walk, with Python

layered_learning_time_series. Layered learning for early anomaly detection in time series

modelradar. Aspect-based Forecasting Accuracy

experiments-cv_selection. Benchmarking Cross-validation Approaches for Model Selection for Time Series Forecasting using Local Models

deprecated-experiments_ade. Experiments with ADE

cardtale. Data Cards for Time Series

experiments-exceedance_cdf. Exceedance Probability Forecasting using CDF

curso_series_temporais. Recursos da disciplina de Séries Temporais

experiments-drift_evaluation. Benchmarking concept drift detection methods

teaching-probabilistic-ai. Materials for course on Probabilistic AI

experiments-tser. Time Series Entity Resampling

experiments-model_compression. Model Compression in Forecasting: Distilling Forecasting Ensembles into a small model

experiments-online_augmentation. Experiments on Online Time Series Data Augmentation