Mastering Diverse Domains through World Models
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Apr 11, 2025 - Python
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Mastering Diverse Domains through 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 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
Dream to Control: Learning Behaviors by Latent Imagination
A curated list of world models for autonomous driving. Keep updated.
DayDreamer: World Models for Physical Robot Learning
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.
A most Frontend Collection and survey of vision-language model papers, and models GitHub repository
World Model based Autonomous Driving Platform in CARLA 🚗
TesserAct: Learning 4D Embodied World Models
《多模态大模型:新一代人工智能技术范式》作者:刘阳,林倞
A structured implementation of MuZero
Code for "DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT"
Implementation of a framework for Genie2 in Pytorch
Implementation of the new SOTA for model based RL, from the paper "Improving Transformer World Models for Data-Efficient RL", in Pytorch
Find and Play Generative Games Locally
A comprehensive list of papers investigating physical cognition in video generation, including papers, codes, and related websites.
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