Amirhossein Arzani
PulseAugur coverage of Amirhossein Arzani — every cluster mentioning Amirhossein Arzani across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
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New framework makes operator learning models self-explainable
Researchers have developed a new self-explainable operator learning framework that enhances the interpretability of neural network models used in functional data analysis. This framework reformulates operator learning i…
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Differentiable physics and PINNs reconstruct wall shear stress
Researchers have developed two inverse frameworks, a differentiable physics approach and physics-informed neural networks (PINNs), to reconstruct wall shear stress (WSS) from passive scalar observations. The study evalu…
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DIANO framework enables interpretable latent spaces for scientific machine learning
Researchers have introduced DIfferentiable Autoencoding Neural Operator (DIANO), a novel framework designed to create interpretable and computationally efficient latent spaces for scientific machine learning. DIANO util…