The Manila Times

WiMi Develops Quantum Convolutional Neural Network Model for Classical Data Classification

WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ('WIMI' or the 'Company'), a leading global Hologram Augmented Reality ('AR') Technology provider, has completed systematic benchmark testing on fully ...
IEEE

Shape Deviation Generator—A Convolution Framework for Learning and Predicting 3-D ...

Abstract: The 3-D shape accuracy is a critical performance measure for products built via additive manufacturing (AM). With advances in computing and increased accessibility of AM product data, ...
IEEE

Deep Residual Learning With Dilated Causal Convolution Extreme Learning Machine

Abstract: A feedforward neural network with random weights (RW-FFNN) uses a randomized feature map layer. This randomization enables the optimization problem to be replaced by a standard linear ...
GitHub

DLPy - SAS Viya Deep Learning API for Python

DLPy is a high-level Python library for the SAS Deep learning features available in SAS Viya. DLPy is designed to provide an efficient way to apply deep learning methods to image, text, and audio data ...
GitHub

Text classification with Convolution Neural Networks (CNN)

Combine word-level with character-based input. The char input ist optional and can be used for further reasearch. Change padding of conv-layer from same to valid. Add average pooling after conv-layer ...
the-decoder

AI-generated CUDA kernels outperform PyTorch in several GPU-heavy machine learning benchmarks

A team at Stanford has shown that large language models can automatically generate highly efficient GPU kernels, sometimes outperforming the standard functions found in the popular machine learning ...
Embedded

Understanding convolutional neural networks

The world of artificial intelligence (AI) is rapidly evolving, and AI is increasingly enabling applications that were previously unattainable or very difficult to implement. A subsequent article, ...
Frontiers

Depthwise separable convolution Unet for 3D seismic data interpolation

In seismic exploration, dense and evenly spatial sampled seismic traces are crucial for successful implementation of most seismic data processing and interpretation algorithms. Recently, numerous ...