DeepONets
PulseAugur coverage of DeepONets — every cluster mentioning DeepONets across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
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New Deep Learning Model Enhances AAA Hemodynamic Prediction
Researchers have developed a novel Modified Multi-Input Multi-Output Physics-Informed DeepONet (M3PI-DeepONet) architecture to more accurately predict complex 3D blood flow dynamics in Abdominal Aortic Aneurysms (AAAs).…
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New DeepONet Framework Enhances Accuracy and Efficiency
Researchers have developed new Fixed and Adaptive Topological DeepONets, which improve upon existing Deep Operator Networks by using continuous linear functionals instead of fixed point values for encoding input functio…
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New theorem advances operator approximation for encoder-decoder neural networks
Researchers have developed a new universal operator approximation theorem specifically for encoder-decoder neural network architectures. This theorem extends existing work by considering a broader range of input and out…
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New hybrid method accelerates MIONet training
Researchers have introduced a novel hybrid least squares/gradient descent (LSGD) method designed to accelerate the training of MIONets. This approach extends existing LSGD techniques used for DeepONets. The method treat…
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Operator Boosting framework creates efficient neural PDE surrogates
Researchers have developed a new framework called Operator Boosting to create more efficient neural network surrogates for solving partial differential equations (PDEs). This method trains smaller neural operators on re…
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AMORE network accelerates stiff chemical kinetics simulations
Researchers have developed AMORE, an Adaptive Multi-Output Operator Network designed to accelerate simulations of stiff chemical kinetics. This framework uses neural operators to predict multiple thermochemical states s…