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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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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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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Simulation-based inference with conditional neural density estimators is a powerful approach to solving inverse problems in science. However, these me...
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Investigates the application of convolutional neural networks (CNNs) for detecting gravitational waves from merging black holes, assessing their poten...
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Cross-platform verification, a critical undertaking in the realm of early-stage quantum computing, endeavors to characterize the similarity of two imp...
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Physics-informed neural networks (PINNs) provide a deep learning framework for numerically solving partial differential equations (PDEs), and have bee...
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