A live map of how every country thinks the 2026 World Cup will go
Visually striking map with 4K+ predictions and zero signup friction.
This repository is the collection of World model Papers
Taxonomy of 489 papers, but GitHub Awesome lists + arXiv already fragment by paradigm.
ML researchers, embodied AI engineers, autonomous driving teams
Papers with Code · arXiv topic collections · Awesome ML curated lists
The literature is increasingly fragmented across RL, diffusion, 3D occupancy forecasting, safety-aware modeling, and autonomous driving.
I put together a structured repository organizing 489 papers (2012–2026) with:
– Dual taxonomy (representation × application) – A visual evolution tree – Venue & trend statistics – 195 open-source implementations
The goal is to organize the field into a coherent map rather than just an aggregated list.
Feedback and missing works are welcome.
Visually striking map with 4K+ predictions and zero signup friction.
Solar position data for stadium seats when SeatGeek and StubHub don't track sun exposure.
Deep historical data viz tracking squad height and age trends since 1930.
Random team picker when Wheel of Names and countless alternatives already exist.
Renaissance parchment aesthetic makes global data exploration feel deliberate.