Adversarial predictive networks By Lukasz Burzawa, Abhishek Chaurasia and Eugenio Culurciello We wanted to test the idea that predictive neural network like CortexNetwould benefit from simultane...

Memory, attention, sequences We have seen the rise and success of categorization neural networks. The next big step in neural network is to make sense of complex spatio-temporal data coming from...

layout: post title: ‘Can We Copy the Brain?’ — Can We Copy the Brain? A review of IEEE Spectrum Special Report: Can We Copy the Brain? The IEEE Spectrum this month has a story on syntheti...

LinkNet: neural networks for autonomous driving From our lab: https://codeac29.github.io/projects/linknet/index.html

e-Lab produtions 1997–2013 See our work in image sensors artificial eyes artificial brains biomedical instrumentation neuroscience instruments https://www.slideshare.net/EugenioCulur...

Neuromorphic and Deep Neural Networks Disclaimer: I have been working on analog and mixed-signal neuromorphic micro-chips during my PhD, and in the last 10 years have switched to Deep Learning and...

A new kind of deep neural networks by Alfredo Canziani, Abishek Chaurasia and Eugenio Culurciello There is a new wave of deep neural networks coming. They are the evolution of feed-forward mode...

Navigating the Unsupervised Learning Landscape Unsupervised learning is the Holy Grail of Deep Learning. The goal of unsupervised learning is to create general systems that can be trained with lit...

Snowflake The most efficient deep neural network accelerator — FWDNXT.com by Vinayak Gokhale, Aliasger Zaidy, Andre Chang, Eugenio Culurciello Deep convolutional neural networks (CNNs) are the d...

Computation and memory bandwidth in deep neural networks Eugenio Culurciello, Aliasger Zaidy and Vinayak Gokhale Memory bandwidth and data re-use in deep neural network computation can be estima...