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Zoom Link: https://hku.zoom.us/j/9174230511?omn=91474809260 Abstract In recent years, deep neural networks (DNNs) have achieved remarkable success across a wide range of applications, especially for low-level image processing. However, many of these approaches rely on complicated and deeply stacked architectures to attain high performance, which lead to significant challenges for deployment on edge devices with limited computing […] |
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Abstract Intelligent reflecting surface (IRS) is envisioned to be a promising 6G technology which changes wireless communications from “adapting to wireless channels” to “changing wireless channels”. However, current IRS configuration schemes, consisting of sub-channel estimation and passive beamforming, are model-based designs and are difficult to be realized in practical and complex radio environment. To create […] |
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Abstract The forthcoming sixth generation (6G) wireless networks will be one of the galvanizing technologies for future advanced and autonomous transportation systems. 6G wireless will provide communication services with stringent requirements which are necessary for autonomous driving and on-flight Internet connectivity. Introduction of AI-empowered 6G would guarantee a more intelligent, efficient and secure transportation system. […] |
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Zoom Link: https://hku.zoom.us/j/92624222498?pwd=5ailfpKH0tFiWDTrt1FUwTOg4bqMnu.1 Abstract Green hydrogen or renewable hydrogen is promising cause it has no carbon emissions in production process, which is water electrolysis with electricity from renewables. Although grids can ensure stable and enough electricity supply, it is difficult to determine whether the grid electricity for hydrogen production is from renewable sources. This article […] |
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🚀 Join the Excitement of Robotics! Competition Details Date: 19 July 2025 (SAT) Time: Check-in begins at 9:00 AM Venue: Innovation Wing One, G/F, Hui Oi Chow Science Building, The University of Hong Kong (HKU) (directions to the venue) Competition Description Engage your autonomous robots in thrilling challenges: - Maze Navigation 迷宮探索 - Rescue […] |
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Abstract Finite symmetric groups Sn are essential in fields such as combinatorics, physics, and chemistry. However, learning a probability distribution over Sn poses significant challenges due to its intractable size and discrete nature. We introduce SymmetricDiffusers, a novel discrete diffusion model that simplifies the task of learning a complicated distribution over Sn by decomposing it […] |
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