Hypernetworks distill modular reservoir connectivity via a genomic bottleneck to generate sparse recurrent networks solving difficult temporal tasks with minimal training and maintained robustness.
Nature Machine Intelligence , volume=
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Meta Agent Search uses a meta-agent to iteratively program novel agentic systems in code, producing agents that outperform state-of-the-art hand-designed ones across coding, science, and math while transferring across domains and models.
NOTES couples a DeepONet topology decoder with CMA-ES in a PCA-derived latent space, achieving >95% deflection efficiency on nanophotonic metagratings and compliance of 246 on MBB beams, outperforming direct CMA-ES and gradient-based baselines.
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Distilling a Modular Reservoir Through a Genomic Bottleneck
Hypernetworks distill modular reservoir connectivity via a genomic bottleneck to generate sparse recurrent networks solving difficult temporal tasks with minimal training and maintained robustness.
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Automated Design of Agentic Systems
Meta Agent Search uses a meta-agent to iteratively program novel agentic systems in code, producing agents that outperform state-of-the-art hand-designed ones across coding, science, and math while transferring across domains and models.
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Neural Operator-enabled Topology-informed Evolutionary Strategy for PDE-Constrained Optimization
NOTES couples a DeepONet topology decoder with CMA-ES in a PCA-derived latent space, achieving >95% deflection efficiency on nanophotonic metagratings and compliance of 246 on MBB beams, outperforming direct CMA-ES and gradient-based baselines.