Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are commi…

Multi-Agent System Powered by LLMs for End-to-end Multimodal ML Automation

AutoMind: Adaptive Knowledgeable Agent for Automated Data Science

[ICML-25] AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML

Source codes of the paper "Hierarchical Pretraining on Multimodal Electronic Health Records".

source codes based on PyTorch to analyze EHR

Experiments for Neural Flows paper

PyTorch Implementation of GRU-D from "Recurrent Neural Networks for Multivariate Time Series with Missing Values" https://arxiv.org/abs/1606.01865

Gated Recurrent Unit with a Decay mechanism for Multivariate Time Series with Missing Values

Code for "Multi-Time Attention Networks for Irregularly Sampled Time Series", ICLR 2021.

An awesome project on irregular time series and incomplete time series

[ICLR 2025] Official implementation of "Expand and Compress: Exploring Tuning Principles for Continual Spatio-Temporal Graph Forecasting"

This is an official repository for "Harnessing Vision Models for Time Series Analysis: A Survey".

[KDD 2025] Awesome Multi-modal Time Series Analysis

A list of (post-hoc) XAI for time series

Official implementation for ICML24 paper "Irregular Multivariate Time Series Forecasting: A Transformable Patching Graph Neural Networks Approach"

Code for our SIGKDD'24 paper GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing

ChatDev 2.0: Dev All through LLM-powered Multi-Agent Collaboration

[ICML 2024] A novel, efficient lightweight approach combining convolutional operations with adaptive spectral analysis as a foundation model for different time series tasks

A Library for Advanced Deep Time Series Models for General Time Series Analysis.

[TKDD 2023] AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series Data

Official repository for the paper "Taming Local Effects in Graph-based Spatiotemporal Forecasting" (NeurIPS 2023)

SAM: Sharpness-Aware Minimization (PyTorch)

Official implementation of SAMformer, a transformer leveraging Sharpness-Aware Minimization and Channel-Wise Attention for Time Series Forecasting.

Official website for "Continual Learning on Graphs: Challenges, Solutions, and Opportunities"

[IJCAI 2024] Official website for "Empowering Time Series Analysis with Large Language Models: A Survey"