Rethinking Temporal Fusion with a Unified Gradient Descent View for 3D Semantic Occupancy Prediction
In autonomous driving, understanding the 3D world over time is critical. Yet, most vision-based 3D Occupancy (VisionOcc) methods only scratch the surface of temporal fusion, focusing on simple ...
Abstract: In Big Data-based applications, high-dimensional and incomplete (HDI) data are frequently used to represent the complicated interactions among numerous nodes. A stochastic gradient descent ...
Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
The agent acquires a vocabulary of neuro-symbolic concepts for objects, relations, and actions, represented through a combination of symbolic programs and neural networks. These concepts are grounded ...
State-of-the-art techniques for pavement performance evaluation have attracted considerable attention in recent years. Artificial Neural Networks (ANNs) can simulate the human brain to discover hidden ...
BAC (Block-wise Adaptive Caching) is a novel acceleration technique designed specifically for Transformer-based Diffusion Policies in robotic manipulation tasks. Our method achieves significant ...
Abstract: Underwater acoustic communication (UAC) is one of the core technologies for the Internet of Underwater Things (IoUT). Channel estimation (CE) is crucial for achieving reliable UAC ...
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