In the era of Vision Transformers and increasingly complex multimodal architectures, convolutional neural networks (ConvNets) have often been written off…
Time-series Forecasting
NeuralForecast: Accurate, Easy-to-Use Neural Time Series Forecasting for Real-World Applications 3883
Time series forecasting remains a core challenge across industries—from retail and energy to finance and logistics. While deep learning has…
TFB: The Fair, Comprehensive Benchmark for Time Series Forecasting That Solves Reproducibility and Bias Problems 1625
Time series forecasting powers critical decisions across industries—from predicting electricity demand and traffic congestion to estimating disease spread and stock…
OpenSTL: A Standardized, Reproducible Benchmark for Spatio-Temporal Forecasting Across Video, Weather, and Traffic Domains 1030
Spatio-temporal predictive learning aims to forecast future states—like video frames, weather maps, or traffic patterns—based solely on past observations, typically…