67 citations · 92 across the 22 of their papers we have counts for
22 papers
The Taxonomies, Training, and Applications of Event Stream Modelling for Electronic Health Records
Mingcheng Zhu, Yu Liu, Zhiyao Luo +1
The widespread adoption of electronic health records (EHRs) enables the acquisition of heterogeneous clinical data, spanning lab tests, vital signs, medications, and procedures, wh…
Standing on the Shoulders of Giants: Rethinking EEG Foundation Model Pretraining via Multi-Teacher Distillation
Chenqi Li, Yu Liu, Shuo Zhang +2
Pretraining for electroencephalogram (EEG) foundation models has predominantly relied on self-supervised masked reconstruction, a paradigm largely adapted from and inspired by the…
BioX-Bridge: Model Bridging for Unsupervised Cross-Modal Knowledge Transfer across Biosignals
Chenqi Li, Yu Liu, Timothy Denison +1
Biosignals offer valuable insights into the physiological states of the human body. Although biosignal modalities differ in functionality, signal fidelity, sensor comfort, and cost…
ProtoEHR: Hierarchical Prototype Learning for EHR-based Healthcare Predictions
Zi Cai, Yu Liu, Zhiyao Luo +1
Digital healthcare systems have enabled the collection of mass healthcare data in electronic healthcare records (EHRs), allowing artificial intelligence solutions for various healt…
Bridging Data Gaps of Rare Conditions in ICU: A Multi-Disease Adaptation Approach for Clinical Prediction
Mingcheng Zhu, Yu Liu, Zhiyao Luo +1
Artificial Intelligence has revolutionised critical care for common conditions. Yet, rare conditions in the intensive care unit (ICU), including recognised rare diseases and low-pr…
OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data
Jinwei Zeng, Yu Liu, Guozhen Zhang +4
Accurately estimating high-resolution carbon emissions is crucial for effective emission governance and mitigation planning. While conventional methods for precise carbon accountin…
SurvUnc: A Meta-Model Based Uncertainty Quantification Framework for Survival Analysis
Yu Liu, Weiyao Tao, Tong Xia +2
Survival analysis, which estimates the probability of event occurrence over time from censored data, is fundamental in numerous real-world applications, particularly in high-stakes…
Generalizing Hyperedge Expansion for Hyper-relational Knowledge Graph Modeling
Yu Liu, Shu Yang, Jingtao Ding +2
By representing knowledge in a primary triple associated with additional attribute-value qualifiers, hyper-relational knowledge graph (HKG) that generalizes triple-based knowledge…
Harnessing the Synergy between LLM Agents and Knowledge Graphs for Urban Socioeconomic Prediction
Zhilun Zhou, Jingyang Fan, Yu Liu +3
Socioeconomic prediction aims to leverage various urban data to predict the socioeconomic indicators of regions such as population and commercial activity level, which plays an imp…
From Pixels to Progress: Generating Road Network from Satellite Imagery for Socioeconomic Insights in Impoverished Areas
Yanxin Xi, Yu Liu, Zhicheng Liu +3
The Sustainable Development Goals (SDGs) aim to resolve societal challenges, such as eradicating poverty and improving the lives of vulnerable populations in impoverished areas. Th…
Estimating On-road Transportation Carbon Emissions from Open Data of Road Network and Origin-destination Flow Data
Jinwei Zeng, Yu Liu, Jingtao Ding +2
Accounting for over 20% of the total carbon emissions, the precise estimation of on-road transportation carbon emissions is crucial for carbon emission monitoring and efficient mit…
UV-SAM: Adapting Segment Anything Model for Urban Village Identification
Xin Zhang, Yu Liu, Yuming Lin +2
Urban villages, defined as informal residential areas in or around urban centers, are characterized by inadequate infrastructures and poor living conditions, closely related to the…
Devil in the Landscapes: Inferring Epidemic Exposure Risks from Street View Imagery
Zhenyu Han, Yanxin Xi, Tong Xia +2
Built environment supports all the daily activities and shapes our health. Leveraging informative street view imagery, previous research has established the profound correlation be…
Towards Generative Modeling of Urban Flow through Knowledge-enhanced Denoising Diffusion
Zhilun Zhou, Jingtao Ding, Yu Liu +2
Although generative AI has been successful in many areas, its ability to model geospatial data is still underexplored. Urban flow, a typical kind of geospatial data, is critical fo…
A Satellite Imagery Dataset for Long-Term Sustainable Development in United States Cities
Yanxin Xi, Yu Liu, Tong Li +5
Cities play an important role in achieving sustainable development goals (SDGs) to promote economic growth and meet social needs. Especially satellite imagery is a potential data s…
OpenSiteRec: An Open Dataset for Site Recommendation
Xinhang Li, Xiangyu Zhao, Yejing Wang +5
As a representative information retrieval task, site recommendation, which aims at predicting the optimal sites for a brand or an institution to open new branches in an automatic d…
Knowledge-infused Contrastive Learning for Urban Imagery-based Socioeconomic Prediction
Yu Liu, Xin Zhang, Jingtao Ding +2
Monitoring sustainable development goals requires accurate and timely socioeconomic statistics, while ubiquitous and frequently-updated urban imagery in web like satellite/street v…
Spatio-Temporal Urban Knowledge Graph Enabled Mobility Prediction
Huandong Wang, Qiaohong Yu, Yu Liu +2
With the rapid development of the mobile communication technology, mobile trajectories of humans are massively collected by Internet service providers (ISPs) and application servic…
Role-Aware Modeling for N-ary Relational Knowledge Bases
Yu Liu, Quanming Yao, Yong Li
N-ary relational knowledge bases (KBs) represent knowledge with binary and beyond-binary relational facts. Especially, in an n-ary relational fact, the involved entities play diffe…
Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases
Yu Liu, Quanming Yao, Yong Li
With the rapid development of knowledge bases (KBs), link prediction task, which completes KBs with missing facts, has been broadly studied in especially binary relational KBs (a.k…
Mobility-aware Caching Scheduling for Fog Computing in mmWave Band
Yong Niu, Yu Liu, Yong Li +3
As an extension of cloud computing, fog computing at the edge of networks provides low latency, location awareness, and real-time interactions. At the same time, millimeter wave (m…
Device-to-Device Communications Enabled Energy Efficient Multicast Scheduling in mmWave Small Cells
Yong Niu, Yu Liu, Yong Li +3
To keep pace with the rapid growth of mobile traffic demands, dense deployment of small cells in millimeter wave (mmWave) bands has become a promising candidate for next generation…