Abstract: Real-world analog systems, such as photonic neural networks, intrinsically suffer from noise that can impede model convergence and accuracy for a variety of deep learning models. In the ...
AZoOptics on MSN
End-to-end differentiable design of geometric waveguide displays
A novel differentiable approach optimizes geometric waveguide coatings, achieving substantial gains in light efficiency and ...
Conditions like A.D.H.D. and autism can make starting and completing tasks feel impossible, but experts say there are workarounds. By Christina Caron The pomodoro technique. Power poses. Planners.
Activation functions play a critical role in AI inference, helping to ferret out nonlinear behaviors in AI models. This makes them an integral part of any neural network, but nonlinear functions can ...
ABSTRACT: The alternating direction method of multipliers (ADMM) and its symmetric version are efficient for minimizing two-block separable problems with linear constraints. However, both ADMM and ...
The original version of this story appeared in Quanta Magazine. Calculus is a powerful mathematical tool. But for hundreds of years after its invention in the 17th century, it stood on a shaky ...
Abstract: Distribution shifts, which often occur in the real world, degrade the accuracy of deep learning systems, and thus improving robustness to distribution shifts is essential for practical ...
Over the last decade, deep generative models have evolved to generate realistic and sharp images. The success of these models is often attributed to an extremely large number of trainable parameters ...
DiffPaSS is a family of high-performance and scalable PyTorch modules for finding optimal one-to-one pairings between two collections of biological sequences, and for performing general graph ...
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