Machine learning methods have recently shown promise in predicting composite material properties more efficiently than traditional finite element simulations. However, in real-world applications of composite materials, variations in filler characteristics or processing conditions can cause a significant mismatch betwee...
A. Bhattacharya, Hang-Wei Qian, Sylvain G. Cloutier et al.· Proceedings of the 32nd ACM...· 0 citations
It is shown that current scientific agents remain insufficiently robust to scientifically plausible perturbations, with failures often remaining undetected, propagating, and resisting recovery.
Xiaoting Lyu, Xin-Bo Ma, Yu-Fei Han et al.· 0 citations
This work reinterpret OOD generalization under covariate shift as a problem of preserving geodesic relationships on the data manifold, and proposes Geometry Support Anchoring (GSA), a geometry-aware learning framework that anchors predictions using geodesic distances to data-dependent reference representations.
Abhiroop Bhattacharya, Hangwei Qian, Sylvain G. Cloutier et al.· Proceedings of the 32nd ACM...· 0 citations
The results suggest that adaptive reasoning should estimate the future value of computation rather than equating present confidence with correctness, and introduce Adaptive Evidence Residual Allocation (AERA), a sequential controller that learns whether additional computation is likely to recover a better answer from c...
This work builds ORDER, a multimodal framework linking microstructures and descriptors with preserved property trends, aiding prediction, retrieval, and microstructure generation and consistently outperforms alignment-oriented and property-aware baselines across property prediction, cross-modal retrieval, and microstru...
Xinyao Li, Hangwei Qian, Jingjing Li et al.· Nature Communications· 0 citations
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