Abstract: By performing computation at the location of data, non-Von Neumann (VN) computing should provide power and speed benefits over conventional (e.g., VN-based) approaches to data-centric ...

In resistor networks, physics computes voltages at selected output nodes automatically and rapidly by exploiting Kirchhoff’s laws when voltages are applied at input nodes. Such networks have been ...

bInternational Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh ...

Although it is in PyTorch, our implementation performs loops across voxels and hence quite slow. Moreover, it takes masks as an input and therefore does not allow backpropagation.

This project replicates the content of Chapter 11 on Transformers in Dive into Deep Learning. It builds an English-French machine translation model using C++. The project develops its own automatic ...

School of Management Engineering, Zhengzhou University of Aeronautics, Zhengzhou 450046, China School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China ...

In deep learning, the standard approach to accommodate changing task demands is to train new output layers on top of a common trunk network, and, if needed, to relearn synapses throughout the whole ...

We developed a deep learning–based algorithm, combining a multilayer perceptron and convolutional neural network, for detecting significant aortic stenosis using ECGs. The developed algorithm achieved ...