1 citations · 1 across the 4 of their papers we have counts for
5 papers
Observation geometry for uncertainty-aware Hamiltonian inference and experimental design in quantum magnets
Roy Liu, Venugopal Ranganathan, David Dahlbom +12
Determining microscopic interactions from spectroscopic and scattering measurements is central to understanding quantum materials, yet it often remains unclear which interactions c…
AIMS: an AI experimentalist turns uncertainty into quantum matter discovery
Siyuan Qiu, Philip D. Suh, Nhat Huy Tran +13
Most AI agents act only after scientists have defined the task. Discovery is harder under practical uncertainties: the probe may not be where it is expected, the signal may occupy…
Multi-resolution Enhancement for Full Spectrum Neural Representations
Yuan Ni, Zhantao Chen, Shizhou Xu +5
Scientific data acquisition continues to outpace storage and analysis capabilities, making voxel-based representations increasingly intractable. Implicit neural representations (IN…
Toward Personalized Darts Training: A Data-Driven Framework Based on Skeleton-Based Biomechanical Analysis and Motion Modeling
Zhantao Chen, Dongyi He, Jin Fang +4
As sports training becomes more data-driven, traditional dart coaching based mainly on experience and visual observation is increasingly inadequate for high-precision, goal-oriente…
Physics-Guided Dual Implicit Neural Representations for Source Separation
Yuan Ni, Zhantao Chen, Alexander N. Petsch +7
Significant challenges exist in efficient data analysis of most advanced experimental and observational techniques because the collected signals often include unwanted contribution…