OpenSTL is a comprehensive benchmark for spatio-temporal predictive learning, encompassing a broad spectrum of methods and diverse tasks, ranging from synthetic moving object trajectories to ...

A growing body of work underlines striking similarities between biological neural networks and recurrent, binary neural networks. A relatively smaller body of work, however, addresses the similarities ...

Application of deep convolutional spiking neural networks (SNNs) to artificial intelligence (AI) tasks has recently gained a lot of interest since SNNs are hardware-friendly and energy-efficient.

This repo contains a sparse learning library which allows you to wrap any PyTorch neural network with a sparse mask to emulate the training of sparse neural networks. It also contains the code to ...

Since its inception in 2014 by Goodfellow et al, generative adversarial networks (GANs) have taken the research community by storm. The business for improving GANs has grown to a point where papers on ...