Duncan Eddy

Uncertainty-aware thresholds slash conjunction screening candidate pairs by up to 71% without missing collisions, outperforming fixed filters and brute-force methods.

Achieving a 53% docking success rate with a world model approach, this research outperforms traditional reinforcement learning methods while demonstrating remarkable generalization capabilities.