When humans write sentences or solve math problems, they are thinking symbolically—each number, variable or word is expressed ...

Perform open vocabulary Class Activation Mapping (CAM), a neural network explainability technique, via CLIP Surgery, a training-free modification to OpenAI's CLIP model.

The volume and variety of enterprise data collected for analytics and AI applications continue to increase. To gain valuable business insights from these complex data assets, organizations are also ...

MATLAB (short for Matrix Laboratory) is a powerful software tool used for technical computing and visualization. It is widely used in a variety of fields, including engineering, science, finance, and ...

A key challenge for systems neuroscience is to understand the coexistence of robustness and sensitivity in neural networks. In particular, a neural system must be robust against perturbations to its ...

Abstract: This article develops a recurrent neural network (RNN) with an encoder–decoder structure to predict the driving sequence of SiC MOSFET active gate drivers (AGDs). With a set of switching ...

Aside from some living tissues, few materials can autonomously learn to exhibit desired behaviors as a consequence of prolonged exposure to unanticipated ambient loading scenarios. Still fewer ...

Rapid progress in technologies such as calcium imaging and electrophysiology has seen a dramatic increase in the size and extent of neural recordings. Even so, interpretation of this data requires ...

Yoshua Bengio, Yann LeCun, and Geoffrey Hinton are recipients of the 2018 ACM A.M. Turing Award for breakthroughs that have made deep neural networks a critical component of computing. Research on ...

The accurate classification of power quality disturbance (PQD) signals is of great significance for the establishment of a real-time monitoring system of modern power grids, ensuring the safe and ...