Find all the Top AIPhysics papers. Links to pdf, code repos and demos are provided.
This monograph proposes a unified theory of 'things' based on statistical independence and Markov blankets, aiming to describe phenomena across variou...
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Models of coupled oscillators are useful in describing a wide variety of
phenomena in physics, biology and economics. These models typically rest on t...
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Introduces the Graph-based Full Event Interpretation (GraFEI), a machine learning model utilizing graph neural networks to reconstruct events at the B...
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Presents a data-driven model demonstrating strong correlations between optical and infrared emissions in galaxies, challenging the conventional assump...
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Introduces TRANSIT, a new model for creating background data templates for weakly-supervised anomaly searches at the LHC, utilizing a transport advers...
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Presents the methodology and outcomes of the Sloan Digital Sky Survey-II Supernova Survey, which efficiently identifies a wide range of transient astr...
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Introduces the Materials Graph Library (MatGL), an open-source graph deep learning library designed for materials science and chemistry applications. ...
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We present a machine learning method for model reduction which incorporates domain-specific physics through candidate functions. Our method estimates ...
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Presents a novel approach to gravitational-wave parameter estimation using deep learning techniques, achieving rapid and precise results. The authors ...
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Recent advances in deep learning have shown that uncertainty estimation is becoming increasingly important in applications such as medical imaging, na...
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We describe a method for removing the effect of confounders in order to
reconstruct a latent quantity of interest. The method, referred to as
half-sib...
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High-contrast imaging of exoplanets hinges on powerful post-processing methods to denoise the data and separate the signal of a companion from its hos...
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