A modular PyTorch library designed for learning, training, and deploying world models across various environments.
DreamerV3 World Model RL from Scratch — Educational implementation of model-based reinforcement learning
Curated papers, code, datasets, and benchmarks for medical world models in imaging, EHR trajectories, treatment planning, surgical AI, robotics, and virtual-cell simulation.
双语技术博客 · 世界模型 / RSSM / DreamerV3 / VLA / Sim-to-Real
Train a neural world model on your own video data, then play it live with WASD. Record → Kaggle → Play
Component-level benchmark for catastrophic forgetting in world models. Two negative results: forgetting does not follow the labelled task-distance axis, and it happens in the encoder, where the usual metrics cannot see it. 375 runs, with code, data and paper.
This project tests that hypothesis using two 1D physical phenomena — heat diffusion and Burgers equation — as elementary World Models, and advection-diffusion as the compound target phenomenon that neither model can represent alone.
Recurrent world models for time-series control, with multi-step rollout training to reduce compounding error.
RSSM world model on a POMDP pendulum with an actor critic trained in imagination. Given equal environment steps the world models beat model-free, at far more compute.
A neural network learns Pac-Man, a world model learns to dream the game, and a third agent learns to play entirely inside those dreams. PPO → RSSM world model → imagination training → online dream loop. Custom vectorized NumPy engine, PyTorch, built from scratch.
RSSM-based world model for latent market dynamics, regime detection, and risk management. DreamerV2-style architecture.
End-to-end home robot navigation with DreamerV3 world models: RSSM latent imagination planning | 基于 DreamerV3 世界模型的居家机器人导航系统
Sonification and visualization of latent space deviations in industrial RSSM models — reconstructing tacit knowledge of skilled workers through data-driven perceptual transduction.
Official implementation for the paper Enhancing Eye Feature Estimation from Event Data Streams through Adaptive Inference State Space Modeling (ETRA '26).
World model (Dreamer/RSSM) vs. model-free PPO for cooperative multi-agent control on PettingZoo Multiwalker with shared policy
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