Vehicular traffic flow simulator in road network, written in pure Python

a workflow engine for Graph-of-Thought

Modeling and control of mixed traffic flow

An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities

Framework for modelling dynamical complex systems

NetworKit is a growing open-source toolkit for large-scale network analysis.

Anonymised human location data for urban mobility research

Official repo for "GeoVista: Web-Augmented Agentic Visual Reasoning for Geolocalization"

Python 3 implementation of the kuramoto model for synchronization of phase oscillators with local and mean-field coupling on a complex network.

Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.

Visualizations of Mittelmann benchmarks

One stop shop for all your GIS Programming needs

Official implement of VGGT-Long

Transform geospatial relations into graph representations designed for spatial network analysis and Graph Neural Networks (GNNs).

Home for all your GPS Tracks: Visualize, share and manage your GPS tracks.

VGGT-SLAM: Dense RGB SLAM Optimized on the SL(4) Manifold

[CVPR 2025 Best Paper Award] VGGT: Visual Geometry Grounded Transformer

[TPAMI 2024] Awesome Resources of GNNs for Time Series Analysis (GNN4TS)

A professional list of Deep Learning and Large (Language) Models (LM, LLM, FM) for Trajectory Data Management and Mining.

Code to generate the results of the paper "The low-rank hypothesis of complex systems".

An open source multi-tool for exploring and publishing data

An Open Platform for Activity-Based Travel Modeling

A tool to visualize complex networks in LaTeX

GEOBench-VLM: Benchmarking Vision-Language Models for Geospatial Tasks

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

This is the homepage of a new book entitled "Mathematical Foundations of Reinforcement Learning."

Reference PyTorch implementation and models for DINOv3

[ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"