A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.
The main features of qingsongedu/awesome-ai-for-time-series-papers are: Awesome List, Research and Surveys.
Open-source alternatives to qingsongedu/awesome-ai-for-time-series-papers include: kimmeen/awesome-gnn4ts — Awesome Graph Neural Networks for Time Series Analysis (GNN4TS). xiaoxinhe/awesome-graph-llm — A collection of AWESOME things about Graph-Related Large Language Models (LLMs). qingsongedu/awesome-ssl4ts — A professionally curated list of awesome resources (paper, code, data, etc.) on Self-Supervised Learning for Time… mooler0410/llmspracticalguide — A curated list of practical guide resources of LLMs (LLMs Tree, Examples, Papers). eugeneyan/open-llms — 📋 A list of open LLMs available for commercial use. bradyfu/awesome-multimodal-large-language-models — :sparkles::sparkles:Latest Advances on Multimodal Large Language Models.
A professionally curated list of awesome resources (paper, code, data, etc.) on Self-Supervised Learning for Time Series (SSL4TS), which is the first work to comprehensively and systematically summarize the recent advances of Self-Supervised Learning for modeling time series data to the best of…
A collection of AWESOME things about Graph-Related Large Language Models (LLMs).
Awesome Graph Neural Networks for Time Series Analysis (GNN4TS)
This project serves as a comprehensive, static directory of external resources dedicated to the study and application of large language models. It functions as a centralized discovery point for developers and researchers, aggregating foundational academic papers, technical documentation, and specialized tools within a structured, version-controlled knowledge base. The repository distinguishes itself through a multi-level classification system that organizes diverse technical domains, ranging from model training frameworks and inference optimization to AI safety and hallucination detection. By