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Found 4 papers, 2 papers with code
Co-orchestration of Multiple Instruments to Uncover Structure-Property Relationships in Combinatorial Libraries
This can be exemplified by the combinatorial libraries that can be explored in multiple locations by multiple tools simultaneously, or downstream characterization in automated synthesis systems.
Human-in-the-loop: The future of Machine Learning in Automated Electron Microscopy
Machine learning methods are progressively gaining acceptance in the electron microscopy community for de-noising, semantic segmentation, and dimensionality reduction of data post-acquisition.
EGraFFBench: Evaluation of Equivariant Graph Neural Network Force Fields for Atomistic Simulations
In addition to our thorough evaluation and analysis on eight existing datasets based on the benchmarking literature, we release two new benchmark datasets, propose four new metrics, and three challenging tasks.
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Discovering mesoscopic descriptions of collective movement with neural stochastic modelling
Collective motion is an ubiquitous phenomenon in nature, inspiring engineers, physicists and mathematicians to develop mathematical models and bio-inspired designs.
