Mastering Diverse Domains through World Models
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Updated
Jul 29, 2024 - Python
Mastering Diverse Domains through World Models
Mastering Atari with Discrete World Models
Transformers are Sample-Efficient World Models. ICLR 2023, notable top 5%.
Dream to Control: Learning Behaviors by Latent Imagination
DayDreamer: World Models for Physical Robot Learning
A comprehensive survey of forging vision foundation models for autonomous driving, including challenges, methodologies, and opportunities.
DIAMOND (DIffusion As a Model Of eNvironment Dreams) is a reinforcement learning agent trained in a diffusion world model.
A structured implementation of MuZero
A curated list of world models for autonomous driving. Keep updated.
World Model based Autonomous Driving Platform in CARLA 🚗
《多模态大模型:新一代人工智能技术范式》作者:刘阳,林倞
Deep Hierarchical Planning from Pixels
World Models applied to the Open AI Sonic Retro Contest
Efficient World Models with Context-Aware Tokenization. ICML 2024
Code for "Planning Goals for Exploration", ICLR2023 Spotlight. An unsupervised RL agent for hard exploration tasks.
Code for the ICLR 2024 spotlight paper: "Learning to Act without Actions" (introducing Latent Action Policies)
Transformer-based World Models
[NeurIPS 2022] SGAM: Building a Virtual 3D World through Simultaneous Generation and Mapping
TrafficBots: Towards World Models for Autonomous Driving Simulation and Motion Prediction. ICRA 2023. You may also want to check out the updated version: https://github.com/zhejz/TrafficBotsV1.5
Recall to Imagine, a model-based RL algorithm with superhuman memory. Oral (1.2%) @ ICLR 2024
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