14/14 By linking data-driven hypothesis generation with hypothesis-driven experiment selection, ATLAS shows real potential to accelerate the discovery of interpretable insights in cognitive science and beyond. Read the full paper here: arxiv.org/abs/2606.12386
- ATLAS combines sparse neural networks with active learning to generate and test mechanistic hypotheses automatically.
- The system achieved 5-10x better sample efficiency than random experimentation across all evaluation metrics.
- Validation compared ATLAS-designed experiments against expert-designed ones from published cognitive science literature.