Neuro-Inspired Inverse Learning for Planning and Control

In three linesNeuro-inspired framework for embodied planning and control. The Inverter uses Inverse Learning (IL) to generate multi-step action sequences. Outperforms offline-RL and diffusion-planner baselines on D4RL (+24.2% average) with 100-1000x less inference compute. Application: single-qubit quantum gate synthesis matching GRAPE fidelity at 1000x faster per-gate compute.

Summary generated by Claude — human-verified