(A) Illustration of a convolutional neural network (NN) whose variational parameters (T) are encoded in the automatically differentiable tensor network (ADTN) shown in (B). The ADTN contains many ...

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

The simplified approach makes it easier to see how neural networks produce the outputs they do. A tweak to the way artificial neurons work in neural networks could make AIs easier to decipher.

An MIT spinoff co-founded by robotics luminary Daniela Rus aims to build general-purpose AI systems powered by a relatively new type of AI model called a liquid neural network. The spinoff, aptly ...