Machine learning techniques that make use of tensor networks could manipulate data more efficiently and help open the black ...

Artificial intelligence has grown so large and power hungry that even cutting edge data centers strain to keep up, yet a technique borrowed from quantum physics is starting to carve these systems down ...

(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 ...

One of the first steps toward becoming a scientist is discovering the difference between speed and velocity. To nonscientists, it’s usually a meaningless distinction. Fast is fast, slow is slow. But ...

Recently, a research group lead by Prof. Shuting Wang from topology optimization of Huazhong University of Science and Technology has put forward a massively efficient filter utilizing the splitting ...

Brian Swingle was a graduate student studying the physics of matter at the Massachusetts Institute of Technology when he decided to take a few classes in string theory to round out his education — ...

Dr. James McCaffrey of Microsoft Research presents the fundamental concepts of tensors necessary to establish a solid foundation for learning how to create PyTorch neural networks, based on his ...