no code implementations • 16 Oct 2024 • Gregorio Marchesini, Siyuan Liu, Lars Lindemann, Dimos V. Dimarogonas
Given a global task expressed as a conjunction of local tasks defined over the individual and relative states of agents in the system, we propose representing task dependencies among agents as edges of a suitably defined task graph.
no code implementations • 24 Sep 2024 • Siyuan Liu, Jiawei Du, Sicheng Xiang, Zibo Wang, Dingsheng Luo
Real-world off-line experiments across eight daily embodied tasks demonstrate that ReLEP is able to accomplish long-horizon embodied tasks and outperforms other state-of-the-art baseline methods.
no code implementations • 11 Sep 2024 • Shengxin Hong, Chang Cai, Sixuan Du, Haiyue Feng, Siyuan Liu, Xiuyi Fan
A case study on 500 critical thinking essays with user studies demonstrates that CAELF significantly improves interactive feedback, enhancing the reasoning and interaction capabilities of LLMs.
no code implementations • 8 Sep 2024 • Gregorio Marchesini, Siyuan Liu, Lars Lindemann, Dimos V. Dimarogonas
We introduce a novel distributed sampled-data control method tailored for heterogeneous multi-agent systems under a global spatio-temporal task with acyclic dependencies.
no code implementations • 29 Jun 2024 • Luyuan Xie, Manqing Lin, Siyuan Liu, Chenming Xu, Tianyu Luan, Cong Li, Yuejian Fang, Qingni Shen, Zhonghai Wu
In medical image segmentation, personalized cross-silo federated learning (FL) is becoming popular for utilizing varied data across healthcare settings to overcome data scarcity and privacy concerns.
no code implementations • 14 Mar 2024 • He Zhang, Chang Liu, Zun Wang, Xinran Wei, Siyuan Liu, Nanning Zheng, Bin Shao, Tie-Yan Liu
Predicting the mean-field Hamiltonian matrix in density functional theory is a fundamental formulation to leverage machine learning for solving molecular science problems.
no code implementations • 27 Feb 2024 • Gregorio Marchesini, Siyuan Liu, Lars Lindemann, Dimos V. Dimarogonas
In this work, we propose a method to decompose signal temporal logic (STL) tasks for multi-agent systems subject to constraints imposed by the communication graph.
no code implementations • 8 Jan 2024 • Qingsi Lai, Fanjie Xu, Lin Yao, Zhifeng Gao, Siyuan Liu, Hongshuai Wang, Shuqi Lu, Di He, LiWei Wang, Cheng Wang, Guolin Ke
XtalNet comprises two modules: a Contrastive PXRD-Crystal Pretraining (CPCP) module that aligns PXRD space with crystal structure space, and a Conditional Crystal Structure Generation (CCSG) module that generates candidate crystal structures conditioned on PXRD patterns.
no code implementations • 3 Jan 2024 • Siyuan Liu, Xiang Yin, Dimos V. Dimarogonas, Majid Zamani
Based on this new system relation, we show that one can verify opacity for stochastic control systems using their abstractions (modeled as finite gMDPs).
no code implementations • 10 Dec 2023 • Xiaoyang Chen, Junjie Zhao, Siyuan Liu, Sahar Ahmad, Pew-Thian Yap
Moreover, this mapping is possible only if the topology of the surface mesh is homotopic to a sphere.
no code implementations • 28 Sep 2023 • He Zhang, Siyuan Liu, Jiacheng You, Chang Liu, Shuxin Zheng, Ziheng Lu, Tong Wang, Nanning Zheng, Bin Shao
Orbital-free density functional theory (OFDFT) is a quantum chemistry formulation that has a lower cost scaling than the prevailing Kohn-Sham DFT, which is increasingly desired for contemporary molecular research.
no code implementations • 23 Sep 2023 • Siyuan Liu, Adnane Saoud, Dimos V. Dimarogonas
This paper considers the problem of controller synthesis of signal temporal logic (STL) specifications for large-scale multi-agent systems, where the agents are dynamically coupled and subject to collaborative tasks.
no code implementations • 5 Jul 2023 • Bingzhuo Zhong, Siyuan Liu, Marco Caccamo, Majid Zamani
These controllers are synthesized based on a concept of so-called (augmented) control barrier functions, which we introduce and discuss in detail.
no code implementations • 21 Mar 2023 • Zehui Dong, Wenjing Liu, Siyuan Liu, Xingzhi Chen
Most of the current research is focusing on class imbalance with a fixed number of classes, while little attention is paid to data imbalance with a variable number of classes.
no code implementations • 3 Jan 2023 • Xiaoyang Chen, Jinjian Wu, Wenjiao Lyu, Yicheng Zou, Kim-Han Thung, Siyuan Liu, Ye Wu, Sahar Ahmad, Pew-Thian Yap
In this paper, we make the first attempt to segment brain tissues across the entire human lifespan (0-100 years of age) using a unified deep learning model.
no code implementations • 24 Dec 2022 • Wenjin Xie, Siyuan Liu, Xiaomeng Wang, Tao Jia
Our proposal performs better in terms of name disambiguation accuracy compared with baselines and the ablation experiments demonstrate the improvement by feature selection and the meta-path level attention in our method.
no code implementations • 8 Nov 2022 • Junyao Hou, Siyuan Liu, Xiang Yin, Majid Zamani
In this paper, we first introduce a concept of approximate pre-opacity by capturing the security level of control systems with respect to the measurement precision of the intruder.
no code implementations • 28 Oct 2022 • Qiang Gao, Xinzhu Zhou, Kunpeng Zhang, Li Huang, Siyuan Liu, Fan Zhou
Stock selection attempts to rank a list of stocks for optimizing investment decision making, aiming at minimizing investment risks while maximizing profit returns.
no code implementations • 22 Sep 2022 • Xiaoyan Liu, Zehui Dong, Zhiwei Xu, Siyuan Liu, Jie Tian
Federated learning (FL) is emerging as a new paradigm to train machine learning (ML) models in distributed systems, including vehicles in V2X networks.
no code implementations • 23 Mar 2022 • Veera Raghava Reddy Kovvuri, Siyuan Liu, Monika Seisenberger, Berndt Müller, Xiuyi Fan
Feature attribution XAI algorithms enable their users to gain insight into the underlying patterns of large datasets through their feature importance calculation.
Explainable Artificial Intelligence (XAI)
Feature Importance
no code implementations • 18 Mar 2022 • Siyuan Liu, Adnane Saoud, Pushpak Jagtap, Dimos V. Dimarogonas, Majid Zamani
In this paper, we focus on the problem of compositional synthesis of controllers enforcing signal temporal logic (STL) tasks over a class of continuous-time nonlinear interconnected systems.
no code implementations • 2 Nov 2021 • Siyuan Liu, Mehmet Orcun Yalcin, Hsuan Fu, Xiuyi Fan
Since the onset of the the COVID-19 pandemic, many countries across the world have implemented various non-pharmaceutical interventions (NPIs) to contain the spread of virus, as well as economic support policies (ESPs) to save their economies.
no code implementations • 29 Oct 2021 • Liang He, Shizhuo Zhang, Lijun Wu, Huanhuan Xia, Fusong Ju, He Zhang, Siyuan Liu, Yingce Xia, Jianwei Zhu, Pan Deng, Bin Shao, Tao Qin, Tie-Yan Liu
The key problem in the protein sequence representation learning is to capture the co-evolutionary information reflected by the inter-residue co-variation in the sequences.
no code implementations • 14 Oct 2021 • Siyuan Liu, Yusong Wang, Tong Wang, Yifan Deng, Liang He, Bin Shao, Jian Yin, Nanning Zheng, Tie-Yan Liu
The identification of active binding drugs for target proteins (termed as drug-target interaction prediction) is the key challenge in virtual screening, which plays an essential role in drug discovery.
no code implementations • 9 Oct 2021 • Siyuan Liu, Kim-Han Thung, Liangqiong Qu, Weili Lin, Dinggang Shen, Pew-Thian Yap
Retrospective artifact correction (RAC) improves image quality post acquisition and enhances image usability.
no code implementations • 30 Sep 2021 • Siyuan Liu, Pew-Thian Yap
Harmonization improves data consistency and is central to effective integration of diverse imaging data acquired across multiple sites.
no code implementations • 24 Sep 2021 • Siyuan Liu, Abdalla Swikir, Majid Zamani
In this work, we propose a compositional framework for the verification of approximate initial-state opacity for networks of discrete-time switched systems.
1 code implementation • 27 Jul 2021 • Xovee Xu, Fan Zhou, Kunpeng Zhang, Siyuan Liu
Second, it learns a generic model for graph cascade tasks via self-supervised contrastive pre-training using both unlabeled and labeled data.
Ranked #1 on
Information Cascade Popularity Prediction
on Weibo
no code implementations • 20 May 2021 • Orcun Yalcin, Xiuyi Fan, Siyuan Liu
In this work, we develop a method to quantitatively evaluate the correctness of XAI algorithms by creating datasets with known explanation ground truth.
no code implementations • 5 Feb 2021 • Siyuan Liu, Navid Noroozi, Majid Zamani
The proposed approach is based on the notion of alternating simulation functions.
no code implementations • 6 Jan 2021 • Yao Li, Tong Wang, Juanrong Zhang, Bin Shao, Haipeng Gong, Yusong Wang, Siyuan Liu, Tie-Yan Liu
We performed molecular dynamics simulation on the S protein with a focus on the function of its N-terminal domains (NTDs).
no code implementations • 5 May 2020 • Xiuyi Fan, Siyuan Liu, Jiarong Chen, Thomas C. Henderson
We compute the top one and two measures that are most effective for the countries and regions studied during the period.
2 code implementations • 5 May 2020 • Xiuyi Fan, Siyuan Liu, Thomas C. Henderson
The overarching goal of Explainable AI is to develop systems that not only exhibit intelligent behaviours, but also are able to explain their rationale and reveal insights.
no code implementations • 7 Apr 2019 • Siyuan Liu, Kim-Han Thung, Weili Lin, Pew-Thian Yap, Dinggang Shen
In this paper, we introduce an image quality assessment (IQA) method for pediatric T1- and T2-weighted MR images.
no code implementations • 23 Jan 2019 • Ke-Wei Huang, Mengke Qiao, Xuanqi Liu, Siyuan Liu, Mingxi Dai
This study provides convincing evidence that the proposed method could objectively create a powerful test statistic based on Q-Q plots and this method could be modified to construct many more powerful test statistics for other applications in the future.
no code implementations • NeurIPS 2018 • Boyla Mainsah, Dmitry Kalika, Leslie Collins, Siyuan Liu, Chandra Throckmorton
Stimulus-driven brain-computer interfaces (BCIs), such as the P300 speller, rely on using a sequence of sensory stimuli to elicit specific neural responses as control signals, while a user attends to relevant target stimuli that occur within the sequence.
1 code implementation • 3 Sep 2018 • Yuan Yuan, Siyuan Liu, Jiawei Zhang, Yongbing Zhang, Chao Dong, Liang Lin
We consider the single image super-resolution problem in a more general case that the low-/high-resolution pairs and the down-sampling process are unavailable.
no code implementations • 27 Aug 2017 • Truc Viet Le, Richard J. Oentaryo, Siyuan Liu, Hoong Chuin Lau
In this work, we address their efficiency issues by proposing local GPs to learn from and make predictions for correlated subsets of data.
1 code implementation • 28 Mar 2016 • Jingbo Zhou, Qi Guo, H. V. Jagadish, Luboš Krčál, Siyuan Liu, Wenhao Luan, Anthony K. H. Tung, Yueji Yang, Yuxin Zheng
We propose a novel generic inverted index framework on the GPU (called GENIE), aiming to reduce the programming complexity of the GPU for parallel similarity search of different data types.