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[TMLR 2025 + ICML 2024 FM-Wild Oral] RouteFinder: Towards Foundation Models for Vehicle Routing Problems
Your own personal AI assistant. Any OS. Any Platform. The lobster way. 🦞
The 500 AI Agents Projects is a curated collection of AI agent use cases across various industries. It showcases practical applications and provides links to open-source projects for implementation…
Recent research papers about Foundation Models for Combinatorial Optimization
Code for the MADDPG algorithm from the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"
[AAAI-26] MPaGE: Pareto-Grid-Guided Large Language Models for Fast and High-Quality Heuristics Design in Multi-Objective Combinatorial Optimization
The official implementation of "RouteExplainer: An Explanation Framework for Vehicle Routing Problem" (PAKDD 2024, oral)
AgentEvolver: Towards Efficient Self-Evolving Agent System
[ICLR 2026] End-to-End Reinforcement Learning for Multi-Turn Tool-Integrated Reasoning
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
SE-Agent is a self-evolution framework for LLM Code agents. It enables trajectory-level evolution to exchange information across reasoning paths via Revision, Recombination, and Refinement, expandi…
本项目旨在分享大模型相关技术原理以及实战经验（大模型工程化、大模型应用落地）
面向开发者的 LLM 入门教程，吴恩达大模型系列课程中文版
"OpenCity: Open Spatio-Temporal Foundation Models for Traffic Prediction"
A Library for Advanced Deep Time Series Models for General Time Series Analysis.
Chronos: Pretrained Models for Time Series Forecasting
Unified Training of Universal Time Series Forecasting Transformers
Code for our CIKM'22 paper Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecasting.
[ICLR 2025 Spotlight] Official implementation of "Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts"
tensorflow实战练习，包括强化学习、推荐系统、nlp等
DeepWalk, build a graph and to get the nodes' vector
Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"
A simple and well styled PPO implementation. Based on my Medium series: https://medium.com/@eyyu/coding-ppo-from-scratch-with-pytorch-part-1-4-613dfc1b14c8.
Adaptive large neighbourhood search (and more!) in Python.