eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

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 ...
IEEE

Trends and Challenges in Computing-in-Memory for Neural Network Model: A Review From Device Design to Application-Side Optimization

Abstract: Neural network models have been widely used in various fields as the main way to solve problems in the current artificial intelligence (AI) field. Efficient execution of neural network ...
IEEE

Comprehensive Design Space Exploration for Graph Neural Network Aggregation on GPUs

Abstract: Graph neural networks (GNNs) have become the state-of-the-art technology for extracting and predicting data representations on graphs. With increasing demand to accelerate GNN computations, ...