Deep learning (DL) is revolutionizing evidence-based decision-making techniques that can
be applied across various sectors. Specifically, it possesses the ability to utilize two or more …

As ChatGPT goes viral, generative AI (AIGC, aka AI-generated content) has made headlines
everywhere because of its ability to analyze and create text, images, and beyond. With such …

Pancreatic cancer is an aggressive disease that typically presents late with poor outcomes,
indicating a pronounced need for early detection. In this study, we applied artificial …

Multi-modality fusion strategy is currently the de-facto most competitive solution for 3D
perception tasks. In this work, we present a new framework termed BEVFormer, which learns …

In this paper, we develop position embedding transformation (PETR) for multi-view 3D
object detection. PETR encodes the position information of 3D coordinates into image …

Transformers have achieved superior performances in many tasks in natural language
processing and computer vision, which also triggered great interest in the time series …

Neural graphics primitives, parameterized by fully connected neural networks, can be costly
to train and evaluate. We reduce this cost with a versatile new input encoding that permits …

In order to drive safely in a dynamic environment, autonomous vehicles should be able to
predict the future states of traffic participants nearby, especially surrounding vehicles, similar …

In the past decade, the application of machine learning (ML) to healthcare has helped drive
the automation of physician tasks as well as enhancements in clinical capabilities and …

We revisit the design choices in Transformers, and propose methods to address their
weaknesses in handling long sequences. First, we propose a simple layer named gated …