world-models

DIAMOND (DIffusion As a Model Of eNvironment Dreams) is a reinforcement learning agent trained in a diffusion world model. NeurIPS 2024 Spotlight.

Mastering Diverse Domains through World Models

Mastering Atari with Discrete World Models

Transformers are Sample-Efficient World Models. ICLR 2023, notable top 5%.

[CVPR 2024 Highlight] GenAD: Generalized Predictive Model for Autonomous Driving & Foundation Models in Autonomous System

Dream to Control: Learning Behaviors by Latent Imagination

DayDreamer: World Models for Physical Robot Learning

A curated list of world models for autonomous driving. Keep updated.

A comprehensive survey of forging vision foundation models for autonomous driving, including challenges, methodologies, and opportunities.

An open source code repository of driving world models, with training, inferencing, evaluation tools, and pretrained checkpoints.

World Model based Autonomous Driving Platform in CARLA 🚗

A structured implementation of MuZero

《多模态大模型：新一代人工智能技术范式》作者：刘阳，林倞

Code for "DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT"

Implementation of a framework for Genie2 in Pytorch

Find and Play Generative Games Locally

Implementation of the new SOTA for model based RL, from the paper "Improving Transformer World Models for Data-Efficient RL", in Pytorch

Efficient World Models with Context-Aware Tokenization. ICML 2024

Deep Hierarchical Planning from Pixels

Code for the ICLR 2024 spotlight paper: "Learning to Act without Actions" (introducing Latent Action Policies)