Abstract: Deep Neural Networks (DNNs) that aim to maximize accuracy and decrease loss can be trained using optimization algorithms. One of the most significant fields of research is the creation of an ...
The test_spectral_embedding_trustworthiness [load_mnist-5000-0.8] test is sometimes failing due to a network connectivity issue when attempting to download the MNIST dataset from OpenML. The test ...
The Generative Medical Imaging Laboratory (GMI) is a comprehensive Python package designed for advanced computational imaging research, with a focus on medical imaging applications. GMI provides a ...
What if you could turn Excel into a powerhouse for advanced data analysis and automation in just a few clicks? Imagine effortlessly cleaning messy datasets, running complex calculations, or generating ...
In view of the growing volume of data, there is a notable research focus on hardware that offers high computational performance with low power consumption. Notably, neuromorphic computing, ...
Harvard University announced Thursday it’s releasing a high-quality dataset of nearly 1 million public-domain books that could be used by anyone to train large language models and other AI tools. The ...
Natural neural systems have inspired innovations in machine learning and neuromorphic circuits designed for energy-efficient data processing. However, implementing the backpropagation algorithm, a ...
This paper presents a new dataset of monetary policy shocks for 21 advanced economies and 8 emerging markets from 2000-2022. We use daily changes in interest rate swap rates around central bank ...
Abstract: Recent studies have demonstrated that deep neural networks show excellent performance in information hiding. Considering the tremendous progress that deep learning has made in image ...
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