10 Best Articles on Neural Networks

Neuroscientists often use neural networks to model the kind of tasks the brain performs, in hopes that the models could suggest new hypotheses regarding how the brain itself performs those tasks. But…

We’ve discovered neurons in CLIP that respond to the same concept whether presented literally, symbolically, or conceptually.

Machine-learning software fills in missing details to produce realistic images.

I sometimes see people refer to neural networks as just “another tool in your machine learning toolbox”.

Large neural networks are at the core of many recent advances in AI, but training them is a difficult engineering and research challenge which requires orchestrating a cluster of GPUs to perform a…

The learning algorithm that enables the runaway success of deep neural networks doesn't work in biological brains, but researchers are finding alternatives that could.

The term “Neural Networks” may seem mysterious, why is an algorithm called Neural Networks? Does it really mimic real neurons, and how?

Neural networks are a subset of machine learning. People exposed to artificial intelligence generally have a good high-level idea about it.

Deep neural networks, often criticized as “black boxes,” are helping neuroscientists understand the organization of living brains.

With new neural network architectures popping up every now and then, it’s hard to keep track of them all. Knowing all the abbreviations being thrown around (DCIGN, BiLSTM, DCGAN, anyone?) can be a bit overwhelming at first. So I decided to compose a cheat sheet containing many of those architectures. Most of these are neural networks, some are completely […]