2 papers
cs.LG2026
Accurate and Efficient World Modeling with Masked Latent Transformers
Maxime Burchi, Radu Timofte
The Dreamer algorithm has recently obtained remarkable performance across diverse environment domains by training powerful agents with simulated trajectories. However, the compress…
cs.LG2025
Learning Transformer-based World Models with Contrastive Predictive Coding
Maxime Burchi, Radu Timofte
The DreamerV3 algorithm recently obtained remarkable performance across diverse environment domains by learning an accurate world model based on Recurrent Neural Networks (RNNs). F…