Serendipitous meetings, scholarly collaborations, and an ethos of "encouraging junior faculty to think big" laid the ...

Researchers from the Institute of Cosmos Sciences of the University of Barcelona (ICCUB) have developed a new framework based ...

Overview A mix of beginner and advanced-level books to suit various learning needs.Each book blends theory with practical ...

Artificial intelligence has taken many forms over the years and is still evolving. Will machines soon surpass human knowledge and understanding?

Deep learning approaches, particularly convolutional neural networks (CNNs) and other architectures, were used in 49 papers. These models excel at image-based tasks such as land cover classification, ...

In today's data-driven environment, Python has become the mainstream language in the fields of machine learning and data science due to its concise syntax, rich library support, and active community, ...

Overview PyTorch and JAX dominate research while TensorFlow and OneFlow excel in large-scale AI trainingHugging Face ...

Abstract: Batch normalization (BN) has proven to be a critical component in speeding up the training of deep spiking neural networks in deep learning. However, conventional BN implementations face ...

1 Institute of Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia 2 Department of Learning, Data Analytics and Technology, Section Cognition, Data and ...

Abstract: Existing methods for integerized training speed up deep learning by using low-bitwidth integerized weights, activations, gradients, and optimizer buffers. However, they overlook the issue of ...