Urban Representation Learning

Latest papers

12 papers1 paper in the last four weeks, down 67% on the four weeks before. 0.0% of all new papers.

Rethinking Multi-View Fusion for Urban Representation Learning
Oct 22, 2026Sean Bin Yang, Zongyi Xu, Jilin Hu +5Urban Representation Learning Multi-View Feature Fusion
Aalborg University, Denmark · Chongqing University of Posts and Telecommunications, China · East China Normal University, China
AlphaEarth distinguishes cities but compresses urban variation
Sep 24, 2026Andrew RenningerGeospatial Foundation Models Geospatial Representation Learning
School of Geographical & Earth Sciences, University of Glasgow
When Correlations Mislead: Confounder-Aware Multi-View Urban Region Representation Learning
Sep 14, 2026Sean Bin Yang, Ying Sun, Zongyi Xu +6Causal Representation Learning Graph Representation Learning
Aalborg University, Aalborg, Denmark · Chongqing University of Posts and Telecommunications, Chongqing, China · East China Normal University, Shanghai, China
Synergistic Fusion of Topological Structure and Temporal Semantics of Mobility for Urban Region Embedding
Sep 8, 2026Namwoo Kim, Jeeyun Chang, Kanghoon Lee +1Feature Interaction Modeling Geospatial Representation Learning
Urban AI Institute, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea · Graduate School of Data Science, KAIST, Daejeon, Republic of Korea · Department of Industrial Engineering and Systems, KAIST, Daejeon, Republic of Korea +1
CoST: Semantic-Aware Urban Understanding via Spatial-Temporal Alignment
Aug 21, 2026Yutian Jiang, Jiabo Liu, Xixuan Hao +1Geospatial Representation Learning Urban Representation Learning
The Hong Kong University of Science and Technology (Guangzhou)
MARCUS: Missing-Aware Region Representation with Contextual Urban Signals for Rent Prediction
Aug 19, 2026Chenya Huang, Bin Liang, Zhidong Li +4Urban Representation Learning Learning with Missing Data
Data Science Institute University of Technology Sydney Sydney, Australia · The Property Investors Alliance Sydney, Australia
MoRAX: Mobility-based Representation Augmentation for Geospatial Foundation Models
Aug 18, 2026Ya Wen, Jixuan Cai, Yulun Zhou +1Representation Learning Geospatial Foundation Models
The University of Hong Kong Hong Kong SAR, China · The Chinese University of Hong Kong Hong Kong SAR, China
A 3D Isovist World Model -- Revealing a City's Unseen Geometry and Its Emergent Cross-City Signature
Jun 2, 2026Xuhui Lin, Stephen Law, Nanjiang Chen +2Representation Learning World Model Learning
Department of Geography University College London, UK · School of Project Management, Faculty of Engineering The University of Sydney, AU · School of Engineering Cardiff University, UK +1
CITYREP: A Unified Benchmark for Urban Representations Across Cities, Tasks, and Modalities
May 25, 2026Junyuan Liu, Xinglei Wang, Zichao Zeng +5Representation Learning Geospatial Representation Learning
SpaceTimeLab, University College London, UK · 3DIMPact, University College London, UK · School of Resource and Environmental Sciences, Wuhan University, China +1
Slum Detection and Density Mapping with AlphaEarth Foundations: A Representation Learning Evaluation Across 12 Global Cities
May 11, 2026Shuyang Hou, Ziqi Liu, Haoyue Jiao +7Geospatial Foundation Models Geospatial Representation Learning
State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, China
Earth Embeddings Reveal Diverse Urban Signals from Space
Apr 3, 2026Wenjing Gong, Udbhav Srivastava, Yuchen Wang +6Geospatial Representation Learning Remote Sensing Benchmarks
Texas A&M University, College Station, TX, USA. · The University of Alabama, Tuscaloosa, AL, USA. · Emory University, Atlanta, GA, USA.
UrbanVerse: Learning Urban Region Representation Across Cities and Tasks
Feb 17, 2026Fengze Sun, Egemen Tanin, Shanika Karunasekera +3Urban Representation Learning Geospatial Representation Learning
School of Computing and Information System, University of Melbourne, Melbourne, Australia · School of Computer Science and Engineering, University of New South Wales, Sydney, Australia

Oct 22, 2026J/K move · Enter open · S save

Rethinking Multi-View Fusion for Urban Representation Learning

Sean Bin Yang, Zongyi Xu, Jilin Hu, Ying Sun+4

Aalborg University, Denmark · Chongqing University of Posts and Telecommunications, China · East China Normal University, China

Urban Representation Learning Multi-View Feature Fusion Representation Learning Multi-View Learning Multi-Task Learning

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Urban region representation learning encodes heterogeneous urban signals, such as mobility flows, points of interest, and land-use patterns, into unified embeddings for downstream tasks, including check-in prediction, crime forecasting, and service demand estimation. Existing approaches rely on globally shared fusion and joint optimization, implicitly assuming uniform modality importance and naturally balanced multi-objective training. However, urban data is inherently heterogeneous. Our empirical analysis reveals two structural issues: (i) modality utility varies markedly across regions, causing static fusion to overemphasize signals from certain modalities; and (ii) heterogeneous objectives exhibit persistent gradient imbalance, causing representational bias and unstable training. We present PRISM, a self-adjusting framework for adaptive multi-view learning. PRISM adapts sparse MoE routing to learn region-specific view allocations, while a PID (Proportional Integral Derivative)-inspired regulation mechanism mitigates gradient conflicts during optimization. Experiments on three large-scale urban datasets show that PRISM achieves competitive performance compared with strong multi-view baselines, while providing more stable optimization behavior and more balanced region representations.