high energy physics
PulseAugur coverage of high energy physics — every cluster mentioning high energy physics across labs, papers, and developer communities, ranked by signal.
1 天有情绪数据
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Transfer learning boosts AI model efficiency in high-energy physics
Researchers have explored transfer learning techniques to improve machine learning model performance in high-energy physics. By pre-training models on computationally cheaper, fast-simulated data and then adapting them …
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Neural networks in physics are vulnerable to hidden systematic errors
Researchers have identified a significant vulnerability in neural network models used for high-energy physics analyses. These models, while powerful, can be systematically misled by subtle input perturbations that remai…
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New frameworks enable asynchronous human-AI collaboration in complex scientific workflows
Researchers have developed HepScript, a Domain-Specific Language (DSL) designed to facilitate human-AI collaboration in high-energy physics data analysis. This DSL abstracts complex analysis logic into a formal syntax t…
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New physics framework links information geometry, jet substructure, and hypergraphs
Researchers have introduced a novel framework that bridges information geometry with jet substructure analysis in high-energy physics. This work demonstrates a triality between cumulant tensors, energy correlators, and …