Explore 20 powerful activation functions for deep neural networks using Python! From ReLU and ELU to Sigmoid and Cosine, ...

Researchers from the University of Tokyo in collaboration with Aisin Corporation have demonstrated that universal scaling ...

Create a fully connected feedforward neural network from the ground up with Python — unlock the power of deep learning!

Classification with Neural Networks Overview This repository contains my implementation of a feed-forward neural network classifier in Python and Keras, trained on the Fashion-MNIST dataset.

The library’s design principles emphasize resolution-agnosticity, ensuring that models trained on one resolution can seamlessly adapt to others, a significant step forward from traditional neural ...

This work will be of interest to the motor control community as well as neuroAI researchers interested in how bodies constrain neural circuit function. The authors present "MotorNet", a useful ...

Recent research has demonstrated that Vision Transformers (ViTs) are capable of comparable or even better performance than convolutional neural network (CNN) baselines. The differences in their ...

The authors present "MotorNet", a useful software package to train artificial neural networks to control a biomechanical model of an effector. The manuscript provides solid evidence that MotorNet is ...