4 citations · 8 across the 16 of their papers we have counts for
17 papers
When Correlations Mislead: Confounder-Aware Multi-View Urban Region Representation Learning
Sean Bin Yang, Ying Sun, Zongyi Xu +6
Urban region representation learning commonly combines heterogeneous data sources, such as mobility flows, points of interest, and land-use information, to support tasks including…
Robustness Analysis of Agentic AI to Inconsistent and Incomplete Tool Responses
Jiachen Xu, Torben Bach Pedersen, Zhongming Yao +2
Tool-using agents increasingly rely on external tools to complete multi-step tasks, but tool returns can fail in different ways and require different recovery actions. Existing rob…
Using Lower-Bound Representations for Trajectory Similarity Learning
Liwei Deng, Haotian Meng, Yupu Zhang +4
Trajectory similarity learning is fundamental to efficient trajectory retrieval under complex distance measures. Existing learning-based methods typically rely on embeddings traine…
Quantum Compression for Distributed Entanglement
Jan Østergaard, Shashi Raj Pandey, Christophe Biscio +2
We study compression strategies for multipartite entanglement distribution under uncertainty in the partitioning of the quantum state. When the partition is not known at the time o…
Reliable AI Needs to Externalize Implicit Knowledge: A Human-AI Collaboration Perspective
Hengyu Liu, Tianyi Li, Zhihong Cui +5
This position paper argues that reliable AI requires infrastructure for human validation of implicit knowledge. AI learns from both explicit knowledge (papers, documentation, struc…
CLEAR: A Knowledge-Centric Vessel Trajectory Analysis Platform
Hengyu Liu, Tianyi Li, Haoyu Wang +5
Vessel trajectory data from the Automatic Identification System (AIS) is used widely in maritime analytics. Yet, analysis is difficult for non-expert users due to the incompletenes…
msData: A Millisecond-Resolution Network Dataset for Advancing Time Series Foundation Models
Subina Khanal, Seshu Tirupathi, Merim Dzaferagic +2
Time series foundation models (TSFMs) require diverse, real-world datasets to adapt across varying domains and temporal frequencies. However, current large-scale datasets predomina…
Advancing Knowledge Tracing by Exploring Follow-up Performance Trends
Hengyu Liu, Yushuai Li, Minghe Yu +6
Intelligent Tutoring Systems (ITS), such as Massive Open Online Courses, offer new opportunities for human learning. At the core of such systems, knowledge tracing (KT) predicts st…
Unraveling Spatio-Temporal Foundation Models via the Pipeline Lens: A Comprehensive Review
Yuchen Fang, Hao Miao, Yuxuan Liang +9
Spatio-temporal deep learning models aims to utilize useful patterns in such data to support tasks like prediction. However, previous deep learning models designed for specific tas…
Extending the SAREF4ENER Ontology with Flexibility Based on FlexOffers
Fabio Lilliu, Amir Laadhar, Christian Thomsen +2
A key element to support the increased amounts of renewable energy in the energy system is flexibility, i.e., the possibility of changing energy loads in time and amount. Many flex…
CAMEO: Autocorrelation-Preserving Line Simplification for Lossy Time Series Compression
Carlos Enrique Muñiz-Cuza, Matthias Boehm, Torben Bach Pedersen
Time series data from a variety of sensors and IoT devices need effective compression to reduce storage and I/O bandwidth requirements. While most time series databases and systems…
Digital Twin-Empowered Voltage Control for Power Systems
Jiachen Xu, Yushuai Li, Torben Bach Pedersen +3
Emerging digital twin technology has the potential to revolutionize voltage control in power systems. However, the state-of-the-art digital twin method suffers from low computation…
Data-Driven Prescriptive Analytics Applications: A Comprehensive Survey
Martin Moesmann, Torben Bach Pedersen
Prescriptive Analytics (PSA), an emerging business analytics field suggesting concrete options for solving business problems, has seen an increasing amount of interest after more t…
Decentralized Multi-Party Multi-Network AI for Global Deployment of 6G Wireless Systems
Merim Dzaferagic, Marco Ruffini, Nina Slamnik-Krijestorac +21
Multiple visions of 6G networks elicit Artificial Intelligence (AI) as a central, native element. When 6G systems are deployed at a large scale, end-to-end AI-based solutions will…
Creating and Querying Data Cubes in Python using pyCube
Sigmundur Vang, Christian Thomsen, Torben Bach Pedersen
Data cubes are used for analyzing large data sets usually contained in data warehouses. The most popular data cube tools use graphical user interfaces (GUI) to do the data analysis…
Domain Adaptation for Time series Transformers using One-step fine-tuning
Subina Khanal, Seshu Tirupathi, Giulio Zizzo +2
The recent breakthrough of Transformers in deep learning has drawn significant attention of the time series community due to their ability to capture long-range dependencies. Howev…
A Comparative Study on Unsupervised Anomaly Detection for Time Series: Experiments and Analysis
Yan Zhao, Liwei Deng, Xuanhao Chen +7
The continued digitization of societal processes translates into a proliferation of time series data that cover applications such as fraud detection, intrusion detection, and energ…