GitHub topics: fully-connected
etrommer/torch-approx
GPU-accelerated Neural Network layers using Approximate Multiplications for PyTorch
Language: Python - Size: 1.93 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 4 - Forks: 3

marchete/Mokka
Mokka is a minimal Inference Engine for Dense and Convolutional 2D Layer Neural Networks. Written on a single C++ header, it uses AVX2
Language: C++ - Size: 1.33 MB - Last synced at: 2 months ago - Pushed at: almost 4 years ago - Stars: 4 - Forks: 3

marchete/NetMokka
Mokka is a minimal Inference Engine for Dense Layer Neural Networks. Written on a single C# header, it uses AVX2
Language: C# - Size: 933 KB - Last synced at: 2 months ago - Pushed at: about 4 years ago - Stars: 5 - Forks: 0

SSQ/Coursera-Ng-Convolutional-Neural-Networks
Language: Python - Size: 57.2 MB - Last synced at: about 2 years ago - Pushed at: over 6 years ago - Stars: 30 - Forks: 44

csbanon/mnist-classifiers
A collection of Jupyter notebooks containing various MNIST digit and fashion item classification implementations using fully-connected and convolutional neural networks (CNNs) built with TensorFlow and Keras. 2020.
Language: Jupyter Notebook - Size: 175 KB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 1

ronggong/deepBach-code-explain
An explanation of deepBach Keras implementation
Size: 75.2 KB - Last synced at: about 2 years ago - Pushed at: about 6 years ago - Stars: 3 - Forks: 3
