IEEE

A Softmax-Free Loss Function Based on Predefined Optimal-Distribution of Latent Features for Deep Learning Classifier

Abstract: In the field of pattern classification, the training of deep learning classifiers is mostly end-to-end learning, and the loss function is the constraint on the final output (posterior ...
GitHub

Angular Penalty Softmax Losses Pytorch

(Note: the SphereFace implementation is not exactly as described in their paper but instead uses the 'trick' presented in the ArcFace paper to use arccosine instead of the double angle formula) There ...
GitHub

Tutorial on the setup and simulation of a membrane protein with AMBER Lipid21 and PACKMOL-Memgen

Disclaimer: I hope this tutorial will be useful to others wishing to run molecular dynamics simulations of membrane proteins with AMBER. However, it is as much for my own reference as a guide to ...
Hosted on MSN

Neural network Python from scratch with softmax

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...
IEEE

Efficient Precision-Adjustable Architecture for Softmax Function in Deep Learning

Abstract: The softmax function has been widely used in deep neural networks (DNNs), and studies on efficient hardware accelerators for DNN have also attracted tremendous attention. However, it is very ...