Researchers have developed a new tool, bimodularity, that adds directionality to community detection in networks.

Neural information extraction algorithms can be trained on data from a few institutions and then can be applied to data from previously unseen hospitals and clinics. This helps to reduce the burden ...

Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning ...

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.

Deep neural networks can solve the most challenging problems, but require abundant computing power and massive amounts of data.

Neuton is a neural network framework, which Bell Integrator claims is far more effective than any other framework and non-neural algorithm available on the market.

If successful, DeepMind's goal to bridge deep learning and classical computer science could revolutionize AI and software as we know them.

Scientists from Tomsk Polytechnic University, together with their colleagues, analyzed various methods of planning experiments to determine the optimal technological parameters of polymer scaffold ...