The attention mechanism is becoming increasingly popular in Natural Language Processing
(NLP) applications, showing superior performance than convolutional and recurrent …

Neural Radiance Field (NeRF) based 3D reconstruction is highly desirable for immersive
Augmented and Virtual Reality (AR/VR) applications, but achieving instant (ie,< 5 seconds) …

HardWare-aware Neural Architecture Search (HW-NAS) has recently gained tremendous
attention by automating the design of DNNs deployed in more resource-constrained daily …

As machine learning and AI continue to rapidly develop, and with the ever-closer end of
Moore's law, new avenues and novel ideas in architecture design are being created and …

Multiplication (eg, convolution) is arguably a cornerstone of modern deep neural networks
(DNNs). However, intensive multiplications cause expensive resource costs that challenge …

Generative adversarial networks (GANs) have gained increasing popularity in various
computer vision applications, and recently start to be deployed to resource-constrained …

An artificial intelligence (AI) processor is a promising solution for energy-efficient data
processing, including health monitoring and image/voice recognition. However, data …

Batch normalization (BN) is a key facilitator and considered essential for state-of-the-art
binary neural networks (BNN). However, the BN layer is costly to calculate and is typically …

Graph Neural Networks (GNNs) have emerged as the state-of-the-art (SOTA) method for
graph-based learning tasks. However, it still remains prohibitively challenging to inference …

The metaverse has recently gained increasing attention from the public. It builds up a virtual
world where we can live as a new role regardless of the role we play in the physical world …