IEEE

Long-Term Time Series Forecasting With Multilinear Trend Fuzzy Information Granules for LSTM in a Periodic Framework

Abstract: Considerable research achievements have been made in utilizing information granulation as an effective technique for addressing long-term time-series forecasting. However, existing studies ...
PCMag on MSN

These 47 expert Excel tricks will transform you into a power user

Microsoft's spreadsheet program can do way more than you might imagine. These are the hacks and tricks you need to know.
GitHub

Is Mamba Effective for Time Series Forecasting?

We propose S-Mamba, a Mamba-based model for time series forecasting, which delegates the extraction of inter-variate correlations and temporal dependencies to a bidirectional Mamba block and a ...

How to Create a Burndown Chart + Free Templates for Agile Teams

Learn how to create burndown charts to track project progress, improve team performance, and download free templates to get ...
IEEE

Self-Supervised Time Series Representation Learning via Cross Reconstruction Transformer

Since labeled samples are typically scarce in real-world scenarios, self-supervised representation learning in time series is critical. Existing approaches mainly employ the contrastive learning ...
GitHub

Time Series Foundation Model - TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

The official code for ["TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting (ICLR 2024)"]. TEMPO is one of the very first open source Time Series Foundation Models for ...