no code implementations • 26 Jan 2024 • Zihao Li, Sixu Li, Hao Zhang, Yang Zhou, Siyang Xie, Yunlong Zhang
While perception systems in Connected and Autonomous Vehicles (CAVs), which encompass both communication technologies and advanced sensors, promise to significantly reduce human driving errors, they also expose CAVs to various cyberattacks.
1 code implementation • 10 Jan 2024 • Sixu Li, Shi Chen, Qin Li
In particular, it has been shown that SGMs can generate samples from a distribution that is close to the ground-truth if the underlying score function is learned well, suggesting the success of SGM as a generative model.
no code implementations • 12 Dec 2023 • Sixu Li, Mohammad Anis, Dominique Lord, Hao Zhang, Yang Zhou, Xinyue Ye
This paper presents a generic analytical framework tailored for surrogate safety measures (SSMs) that is versatile across various highway geometries, capable of encompassing vehicle dynamics of differing dimensionality and fidelity, and suitable for dynamic, real-world environments.
no code implementations • 25 Nov 2023 • Sixu Li, Yang Zhou, Xinyue Ye, Jiwan Jiang, Meng Wang
Subsequently, the lower-level control employs a longitudinal distributed model predictive control (MPC) supplemented by a virtual car-following (CF) concept to ensure asymptotic local stability, l_2 norm string stability, and safety.
no code implementations • 19 Sep 2023 • Yonggan Fu, Yongan Zhang, Zhongzhi Yu, Sixu Li, Zhifan Ye, Chaojian Li, Cheng Wan, Yingyan Lin
To our knowledge, this work is the first to demonstrate an effective pipeline for LLM-powered automated AI accelerator generation.
no code implementations • 9 May 2023 • Yang Zhao, Shang Wu, Jingqun Zhang, Sixu Li, Chaojian Li, Yingyan Lin
Instant on-device Neural Radiance Fields (NeRFs) are in growing demand for unleashing the promise of immersive AR/VR experiences, but are still limited by their prohibitive training time.
1 code implementation • 4 May 2023 • Jose A. Carrillo, Nicolas Garcia Trillos, Sixu Li, Yuhua Zhu
Federated learning is an important framework in modern machine learning that seeks to integrate the training of learning models from multiple users, each user having their own local data set, in a way that is sensitive to data privacy and to communication loss constraints.
no code implementations • 24 Apr 2023 • Yonggan Fu, Zhifan Ye, Jiayi Yuan, Shunyao Zhang, Sixu Li, Haoran You, Yingyan Lin
Novel view synthesis is an essential functionality for enabling immersive experiences in various Augmented- and Virtual-Reality (AR/VR) applications, for which generalizable Neural Radiance Fields (NeRFs) have gained increasing popularity thanks to their cross-scene generalization capability.
1 code implementation • 13 Oct 2022 • Aditya Kumar Akash, Sixu Li, Nicolás García Trillos
In our framework, the fusion occurs in a layer-wise manner and builds on an interpretation of a node in a network as a function of the layer preceding it.
no code implementations • 27 Oct 2020 • Bin Xu, Junzhe Shi, Sixu Li, Huayi Li, Zhe Wang
Then, the result from a vehicle without ultracapacitor is used as the baseline, which is compared with the results from the vehicle with ultracapacitor using Q-learning, and two heuristic methods as the energy management strategies.