Layered metasurfaces trained as optical neural networks enable multifunctional holograms and security features, integrating neural computation principles with nanostructured optics to create a ...
For the preparation of high-dimensional functions on quantum computers, we introduce tensor network algorithms that are efficient with regard to dimensionality, optimize circuits composed of ...
Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is the ...
Function secret sharing (FSS) is a secret sharing technique for functions in a specific function class, mainly including distributed point function (DPF) and distributed comparison function (DCF). As ...
When I try to compute gradients with a kernel calling a function that calls a function that has custom gradients, I get a compiler error. A direct call of the custom ...
Forbes contributors publish independent expert analyses and insights. I’m a founder, writer and lecturer focusing on VC funds. A photo taken on January 2, 2025 shows the letters AI for Artificial ...
ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...
Learn to choose coordinate systems, visualize multivariable functions, and parameterize curves. You can use these live scripts as demonstrations in lectures, class activities, or interactive ...
A new technical paper titled “Computing high-degree polynomial gradients in memory” was published by researchers at UCSB, HP Labs, Forschungszentrum Juelich GmbH, and RWTH Aachen University.
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