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Relevant bibliographies by topics / Spatio-Temporal heterogeneity

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Academic literature on the topic 'Spatio-Temporal heterogeneity'

Author: Grafiati

Published: 15 June 2024

Last updated: 31 July 2025

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Journal articles on the topic "Spatio-Temporal heterogeneity"

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Li, Zetao, Zheng Hu, Peng Han, Yu Gu, and Shimin Cai. "SSL-STMFormer Self-Supervised Learning Spatio-Temporal Entanglement Transformer for Traffic Flow Prediction." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 11 (2025): 12130–38. https://doi.org/10.1609/aaai.v39i11.33321.

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Traffic flow prediction remains a critical issue in intelligent transport systems. Despite significant efforts in traffic flow modeling, existing approaches exhibit several notable limitations: (i) Most models fail to capture traffic flow similarities over long distances and extended periods; (ii) They struggle to account for spatio-temporal heterogeneity induced by varying traffic flow patterns; (iii) Due to their static modeling approach, they struggle to effectively capture the intricate spatio-temporal entanglement. To address these challenges, we propose a traffic flow prediction framewor

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Song, Jianxiang, Jiafu Liu, Xinyue Zhang, Xin Chen, Yingtao Shang, and Fengjie Gao. "Spatio-Temporal Fluctuation Analysis of Ecosystem Service Values in Northeast China over Long Time Series: Based on Bayesian Hierarchical Modeling." Land 13, no. 6 (2024): 833. http://dx.doi.org/10.3390/land13060833.

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Ecosystems are undergoing continuous degradation due to the dual perturbation of global climate change and human activities, posing unprecedented threats and challenges to the ecosystem services they provide. To gain a deeper understanding of the spatio-temporal evolution of ecosystem service value (ESV), it is essential to accurately capture the characteristics of its spatial and temporal changes and its influencing factors. However, traditional spatio-temporal statistical methods are limited to analyzing the heterogeneity of ESV in a single temporal or spatial dimension, which fails to meet

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Liu, Qingxiang, Sheng Sun, Yuxuan Liang, Min Liu, and Jingjing Xue. "Personalized Federated Learning for Spatio-Temporal Forecasting: A Dual Semantic Alignment-Based Contrastive Approach." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 11 (2025): 12192–200. https://doi.org/10.1609/aaai.v39i11.33328.

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The existing federated learning (FL) methods for spatio-temporal forecasting fail to capture the inherent spatio-temporal heterogeneity, which calls for personalized FL (PFL) methods to model the spatio-temporally variant representations. While contrastive learning is promising in tackling spatio-temporal heterogeneity, the existing methods are noneffective in distinguishing positive and negative pairs and can hardly apply to PFL paradigm. To tackle this limitation, we propose a novel PFL method, named Federated dUal sEmantic aLignment-based contraStive learning (FUELS), which can adaptively a

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Scarrott, Rory Gordon, Fiona Cawkwell, Mark Jessopp, Caroline Cusack, Eleanor O’Rourke, and C. A. J. M. de Bie. "Ocean-Surface Heterogeneity Mapping (OHMA) to Identify Regions of Change." Remote Sensing 13, no. 7 (2021): 1283. http://dx.doi.org/10.3390/rs13071283.

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Mapping heterogeneity of the ocean’s surface waters is important for understanding biogeographical distributions, ocean surface habitat mapping, and ocean surface stability. This article describes the Ocean-surface Heterogeneity MApping (OHMA) algorithm—an objective, replicable approach that uses hypertemporal, satellite-derived datasets to map the spatio-temporal heterogeneity of ocean surface waters. The OHMA produces a suite of complementary datasets—a surface spatio-temporal heterogeneity dataset, and an optimised spatio-temporal classification of the ocean surface. It was demonstrated her

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Ji, Jiahao, Jingyuan Wang, Chao Huang, et al. "Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 4 (2023): 4356–64. http://dx.doi.org/10.1609/aaai.v37i4.25555.

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Robust prediction of citywide traffic flows at different time periods plays a crucial role in intelligent transportation systems. While previous work has made great efforts to model spatio-temporal correlations, existing methods still suffer from two key limitations: i) Most models collectively predict all regions' flows without accounting for spatial heterogeneity, i.e., different regions may have skewed traffic flow distributions. ii) These models fail to capture the temporal heterogeneity induced by time-varying traffic patterns, as they typically model temporal correlations with a shared p

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Feng, Jian, Cailing Du, and Qi Mu. "Traffic Flow Prediction Based on Federated Learning and Spatio-Temporal Graph Neural Networks." ISPRS International Journal of Geo-Information 13, no. 6 (2024): 210. http://dx.doi.org/10.3390/ijgi13060210.

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In response to the insufficient consideration of spatio-temporal dependencies and traffic pattern similarity in traffic flow prediction methods based on federated learning, as well as the neglect of model heterogeneity and objective heterogeneity, a traffic flow prediction model based on federated learning and spatio-temporal graph neural networks is proposed. The model is divided into two stages. In the road network division stage, the traffic road network is divided into subnetworks by the dynamic time warping algorithm and the K-means algorithm, to ensure the same subnetwork has the similar

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Atkinson, Peter M. "Pierre Dutilleul: Spatio-temporal Heterogeneity: Concepts and Analyses." Mathematical Geosciences 46, no. 4 (2014): 513–15. http://dx.doi.org/10.1007/s11004-014-9528-z.

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Zhao, Bin, Gusheng Wu, Junjie Li, Qianhong Wu, and Min Deng. "Spatio-Temporal Heterogeneous Ensemble Learning Method for Predicting Land Subsidence." Applied Sciences 14, no. 18 (2024): 8330. http://dx.doi.org/10.3390/app14188330.

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The prediction of land subsidence is of significant value for the early warning and prevention of geological disasters. Although numerous land subsidence prediction methods are currently available, two obstacles still exist: (i) spatio-temporal heterogeneity of land subsidence is not well considered, and (ii) the prediction performance of individual models is unsatisfactory when the data do not meet their assumptions. To address these issues, we developed a spatio-temporal heterogeneous ensemble learning method for predicting land subsidence. Firstly, a two-stage hybrid spatio-temporal cluster

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Ren, Siyuan, Bin Guo, Qinfen Wang, and Zhiwen Yu. "Non-IID spatio-temporal prediction in smart cities." XRDS: Crossroads, The ACM Magazine for Students 28, no. 3 (2022): 38–41. http://dx.doi.org/10.1145/3522692.

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Non-IID spatio-temporal prediction research points toward emerging directions and fundamental solutions to address various complexities from the perspective of both data couplings and heterogeneity. Delving into the non-IID challenge and opportunity of spatio-temporal prediction in smart cities, this article also addresses current solutions to bring some inspiration to future researchers.

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Zhang, Huibing, Qianxin Xie, Zhaoyu Shou, and Yunhao Gao. "Dynamic Spatial-Temporal Memory Augmentation Network for Traffic Prediction." Sensors 24, no. 20 (2024): 6659. http://dx.doi.org/10.3390/s24206659.

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Traffic flow prediction plays a crucial role in the development of smart cities. However, existing studies face challenges in effectively capturing spatio-temporal contexts, handling hierarchical temporal features, and understanding spatial heterogeneity. To better manage the spatio-temporal correlations inherent in traffic flow, we present a novel model called Dynamic Spatio-Temporal Memory-Augmented Network (DSTMAN). Firstly, we design three spatial–temporal embeddings to capture dynamic spatial–temporal contexts and encode the unique characteristics of time units and spatial states. Secondl

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Dissertations / Theses on the topic "Spatio-Temporal heterogeneity"

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Mazzola, Monica B. "Spatio-temporal heterogeneity and habitat invasibility [sic] sagebrush steppe ecosystems." abstract, 2008. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3307539.

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Afán, Asencio Isabel. "Ecological response of marine predators to environmental heterogeneity and spatio-temporal variability in resource availability." Doctoral thesis, Universitat de Barcelona, 2016. http://hdl.handle.net/10803/398990.

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Seabirds have evolved within an open and dynamic environment, the ocean. As meso-top predators, seabirds are greatly influenced by the oceanographic conditions driving marine productivity, and therefore, distribution of their prey. Consequently, seabirds’ behaviour and, ultimately, life-history traits are greatly influenced, by the ever-changing oceanographic conditions. However, oceanographic conditions are currently changing at ever-increasing rates due to global warming and human harvest impacting marine ecosystems. Thus, seabirds have become particularly vulnerable to these changes. Accord

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He, Qian. "Spatio-Temporal Patterns, Correlations, and Disorder in Evolutionary Game Theory." Diss., Virginia Tech, 2011. http://hdl.handle.net/10919/40296.

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Evolutionary game theory originated from the application of mathematical game theory to biological studies. Well-known examples in evolutionary game theory are the prisoner's dilemma, predator-prey models, the rock-paper-scissors game, etc. Recently, such well-known models have attracted increased interest in population dynamics to understand the emergence of biodiversity and species coexistence. Meanwhile, it has been realized that techniques from statistical physics can aid us to gain novel insights into this interdisciplinary field. In our research, we mainly employ individual-based Mo

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Umakhanthan, Kanagaratnam Civil &amp Environmental Engineering Faculty of Engineering UNSW. "Estimation of the spatio-temporal heterogeneity of rainfall and its importance towards robust catchment simulation, within a hydroinformatic environment." Awarded by:University of New South Wales. School of Civil and Environmental Engineering, 2002. http://handle.unsw.edu.au/1959.4/18668.

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Rainfall is a natural process, which has a high degree of variability in both space and time. Information on the spatial and temporal variability of rainfall plays an important role in the process of surface runoff generation. Hence it is important for a variety of applications in hydrology and water resources management. The spatial variability of rainfall can be substantial even for very small catchments and an important factor in the reliability of rainfall-runoff simulations. Catchments in urban areas usually are small, and the management problems often require the numerical simulation of

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Lambert, Charlotte. "Top predators in marine ecosystem : their response to ocean spatio-temporal variability." Thesis, La Rochelle, 2016. http://www.theses.fr/2016LAROS010/document.

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Le milieu marin est un espace difficile à étudier et notre connaissance des cétacés et des oiseaux marins présente encore de nombreuses lacunes, notamment concernant leur distribution au large. Le milieu marin pélagique est caractérisé par une forte variabilité spatiotemporelle, les différents processus écologiques composant cet écosystème étant très dynamiques dans le temps et l'espace. Il est donc crucial pour ces espèces marines d'anticiper ces variations afin de se maintenir dans le milieu. Grâce à des campagnes en mer à grandes échelles réalisées en Manche, Golfe de Gascogne et Méditerran

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Guo, Dali. "Spatio-temporal patterns of soil resources following disturbance in a 40-year-old slash pine (pinus elliottii Engelm.) forest in the Coastal Plain of South Carolina." Diss., Virginia Tech, 2001. http://hdl.handle.net/10919/29346.

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There has been an increased interest in characterizing and interpreting ecological heterogeneity over space and time in the past two decades. This is mainly due to the renewed recognition of the significance of heterogeneity in ecological theories. However, studies that have combined both spatial and temporal aspects of heterogeneity have been rare. A unified approach to define and quantify heterogeneity has also been lacking. Designed to overcome these problems, this study was conducted in a 40-year-old Pinus elliottii Engelm. forest at the Savannah River Site near Aiken, SC, USA with th

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Olazcuaga, Laure. "Réponses adaptatives chez Drosophila suzukii, une espèce généraliste envahissante." Electronic Thesis or Diss., Montpellier, SupAgro, 2019. http://www.theses.fr/2019NSAM0045.

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Comprendre comment évolue l’adéquation entre le phénotype des organismes et leur environnement est un enjeu majeur de la biologie évolutive, notamment dans le contexte des changements globaux. Dans le cadre de cette thèse, j’ai étudié les réponses adaptatives aux pressions environnementales, à différentes échelles géographiques et temporelles de Drosophila suzukii, une espèce généraliste envahissante ravageuse des cultures fruitières. J’ai utilisé des méthodes de génétique évolutive combinant génomique des populations et approches expérimentales centrées sur l’étude des traits d’histoire de vi

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Smucker, Nathan J. "Using Diatoms and Biofilms to Assess Agricultural and Coal Mining Impacts on Streams, Spatio-Temporal Variability, and Successional Processes." Ohio University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1276285170.

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Umakhanthan, K. "Estimation of the spatio-temporal heterogeneity of rainfall and its importance towards robust catchment simulation, within a hydroinformatic environment /." 2002. http://www.library.unsw.edu.au/~thesis/adt-NUN/public/adt-NUN20030217.121039/index.html.

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Books on the topic "Spatio-Temporal heterogeneity"

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Spatio-temporal heterogeneity: Concepts and analyses. Cambridge University Press, 2011.

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Miguel, Eve, Florence Fournet, Serge Yerbanga, et al. Optimizing public health strategies in low-income countries: epidemiology, ecology and evolution for the control of malaria. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198789833.003.0016.

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During the 20th century, health inequalities among countries have increased. Several factors explain this pattern, such as immunization and massive antibiotherapy, but nutrition, housing and hygiene are key parameters for health improvement. This heterogeneity among countries is well illustrated by malaria, although disappeared from many high-income countries, is still endemic and prevalent in low- and middle-income countries. We question these differences and detail the recommendations proposed by the World Health Organization to tackle malaria. We investigate the optimal combination of actio

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Book chapters on the topic "Spatio-Temporal heterogeneity"

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Kaushik, Saurabh, Pawan Kumar Joshi, Tejpal Singh, and Mohd Farooq Azam. "Spatio-Temporal Heterogeneity in Glaciers Response Across Western Himalaya." In Mountain Landscapes in Transition. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70238-0_4.

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Tran, Ba-Huy, Christine Plumejeaud-Perreau, Alain Bouju, and Vincent Bretagnolle. "A Semantic Mediator for Handling Heterogeneity of Spatio-Temporal Environment Data." In Communications in Computer and Information Science. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24129-6_33.

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Wang, Yili, Jiamin Chen, Qiutong Li, Changlong He, and Jianliang Gao. "Relation Time-Aware Heterogeneous Dynamic Graph Neural Networks." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2024. http://dx.doi.org/10.3233/faia240699.

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Heterogeneous dynamic graph neural networks (HDGNNs) are effective methods for processing heterogeneous temporal graphs (HTGs), which serve as ubiquitous data structures in real-world scenarios. The previous HDGNN paradigm obtains representations of future target nodes by mining the spatial heterogeneity and temporal dependence of node attributes, ignoring the learning of relation temporal dependence. However, through experience, we find that the learning of relation temporal dependence, which describes the evolving trends in the importance of neighbors under a certain relation, is beneficial

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Freemark, Kathryn E., John B. Dunning, Sallie J. Hejl, and John R. Probst. "A Landscape Ecology Perspective For Research, Conservation, And Management." In Ecology And Management Of Neotropical Migratory Birds. Oxford University PressNew York, NY, 1995. http://dx.doi.org/10.1093/oso/9780195084405.003.0014.

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Abstract It is becoming increasingly clear that the distribution and population dynamics of Neotropical migratory birds cannot be under stood solely from processes occurring within individual habitat patches. Effects from the surrounding landscape also have to be considered. The need for a landscape perspective in conservation and management has been explicitly recognized in the eco system management approach being developed by the USDA Forest Service (Kessler et al. 1992 and related papers in the same issue) and is currently being evaluated in the Pacific Northwest (Franklin 1989, Hansen et a

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Joshi, P. K., and Neena Priyanka. "Geo-Informatics for Land Use and Biodiversity Studies." In Geographic Information Systems. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2038-4.ch114.

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The dynamics of land use/land cover (LU/LC) is a manifestation of the cyclic correlation among the kind and magnitude of causes, impacts, responses and resulting ecological processes of the ecosystem. Thus, the holistic understanding of the complex mechanisms that control LU/LC requires synergetic adoption of measurement approaches, addressing issues, and identifying drivers of change and state of art technologies for mitigation measures. As the spatio-temporal heterogeneity of the LU/LC increases, its impact on biodiversity becomes even more difficult to anticipate. Thus, in order to understa

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Sturman, Andrew, and Hervé Quénol. "Urban Environments, Air Pollution, and Human Health." In Climate Change. Oxford University Press, 2023. http://dx.doi.org/10.1093/hesc/9780198807506.003.0003.

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This chapter explores the interplay of urban environments, air pollution, and human health. Intensive urbanization and related commercial and industrial activity have caused significant reductions in air quality. Essentially, the spatio-temporal variability of urban climate is the result of very strong heterogeneity of urbanized space. Urban air pollution refers to the atmospheric constituents in urban areas that are modified, which have detrimental impacts on human health and the environment. The chapter considers the impact of climate change on the urban environment, such as a rise in the se

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Glowczewski, Barbara. "A Topological Approach to Australian Cosmology and Social Organisation." In Indigenising Anthropology with Guattari and Deleuze. Edinburgh University Press, 2019. http://dx.doi.org/10.3366/edinburgh/9781474450300.003.0007.

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Aboriginal kinship has stimulated many mathematicians. In the 1980’s, Glowczewski showed that there is a non euclidian ‘topologic’ that is common to what Indigenous Australians call their “Law”: a non hierarchical system of classificatory ritual kinship, a projection of the mythical travels of totemic ancestors (the Dreamings) into the landscape and a system of ritual obligations taboos. In other words, the social valorisation of heterogeneity recognises irreducible singularities shared by humans, non humans and the land as a condition for a commons that in no way homogenises society into a hi

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Faucon, Térésa. "Godard’s suburban years." In Screening the Paris suburbs. Manchester University Press, 2018. http://dx.doi.org/10.7228/manchester/9781526106858.003.0011.

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Far from a simple backdrop, the lived environment was for Jean-Luc Godard capable of eliciting specific modes of cinematographic thought; choice of locations could impact the shape and feel of a film more than its screenplay. Prevalent in his works of the 1960s are suburban landscapes and locales, from the villas, cafés and roadways frequented by the characters of Bande à part (1964) to the high-rises of La Courneuve shown in the essay in phenomenology 2 ou 3 choses que je sais d’elle (1967). Without positing an equivalence between suburban heterogeneity and Godard’s jarring late-modern aesthe

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Conference papers on the topic "Spatio-Temporal heterogeneity"

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Deng, Jiewen, Renhe Jiang, Jiaqi Zhang, and Xuan Song. "Multi-Modality Spatio-Temporal Forecasting via Self-Supervised Learning." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/223.

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Multi-modality spatio-temporal (MoST) data extends spatio-temporal (ST) data by incorporating multiple modalities, which is prevalent in monitoring systems, encompassing diverse traffic demands and air quality assessments. Despite significant strides in ST modeling in recent years, there remains a need to emphasize harnessing the potential of information from different modalities. Robust MoST forecasting is more challenging because it possesses (i) high-dimensional and complex internal structures and (ii) dynamic heterogeneity caused by temporal, spatial, and modality variations. In this study

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Hu, Shihui, Xinmeng Wan, and Danhuai Guo. "Spatio-temporal Heterogeneity Analysis of Transportation Equity Based on GTWR." In SIGSPATIAL '23: The 31st ACM International Conference on Advances in Geographic Information Systems. ACM, 2023. http://dx.doi.org/10.1145/3615884.3629432.

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Zhang, Yu, Hua Lu, Ning Liu, Yonghui Xu, Qingzhong Li, and Lizhen Cui. "Personalized Federated Learning for Cross-City Traffic Prediction." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/611.

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Traffic prediction plays an important role in urban computing. However, many cities face data scarcity due to low levels of urban development. Although many approaches transfer knowledge from data-rich cities to data-scarce cities, the centralized training paradigm cannot uphold data privacy. For the sake of inter-city data privacy, Federated Learning has been used, which follows a decentralized training paradigm to enhance traffic knowledge of data-scarce cities. However, spatio-temporal data heterogeneity causes client drift, leading to unsatisfactory traffic prediction performance. In this

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Zhen, Andrew, Minjeong Kim, and Guorong Wu. "Disentangling The Spatio-Temporal Heterogeneity of Alzheimer’s Disease Using A Deep Predictive Stratification Network." In 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI). IEEE, 2021. http://dx.doi.org/10.1109/isbi48211.2021.9433903.

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Diaz, M. B., G. W. Lee, S. Yun, and K. Y. Kim. "Spatio-Temporal Evolution of Swelling Behavior of Gyeongju Bentonite Under Hydration Process." In 57th U.S. Rock Mechanics/Geomechanics Symposium. ARMA, 2023. http://dx.doi.org/10.56952/arma-2023-0854.

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ABSTRACT Gyengju bentonite has been suggested as a candidate material for buffer and backfill in high-level radioactive waste repository facilities in South Korea. Under the influence of environmental conditions such as thermal, hydrological, and mechanical processes, it is essential to investigate the behavior of these materials. In this study we assessed the swelling behavior of KJ-II Gyeongju bentonite under hydration using X-ray CT technology. A cylindrical sample of 27.5 mm in diameter and 34 mm in height using was utilized in a tailor-made hydration cell, and water was injected at a cons

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Mumenthaler, Shannon, Jasmine Foo, Nathan Choi, et al. "Abstract PR16: Spatio-temporal heterogeneity in the tumor microenvironment influences the evolutionary dynamics of drug resistance." In Abstracts: AACR Special Conference on Cellular Heterogeneity in the Tumor Microenvironment; February 26 — March 1, 2014; San Diego, CA. American Association for Cancer Research, 2015. http://dx.doi.org/10.1158/1538-7445.chtme14-pr16.

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Khurana, Swamini, Falk Heße, and Martin Thullner. "Influence of Spatio-Temporal Heterogeneity on Biogeochemical Cycling in the Subsurface Using a Numerical Modeling Approach." In Goldschmidt2020. Geochemical Society, 2020. http://dx.doi.org/10.46427/gold2020.1291.

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Gil-Bernabe, Sara, Noa Feas Rodríguez, Miriam Vega Herrero, Jose Javier Estébanez García, and Ginesa M. Garcia-Rostan. "Abstract 2770: Spatio-temporal genetic heterogeneity and clonal evolution in advanced papillary thyroid carcinomas and matched distant metastases." In Proceedings: AACR Annual Meeting 2019; March 29-April 3, 2019; Atlanta, GA. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1538-7445.sabcs18-2770.

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Gil-Bernabe, Sara, Noa Feas Rodríguez, Miriam Vega Herrero, Jose Javier Estébanez García, and Ginesa M. Garcia-Rostan. "Abstract 2770: Spatio-temporal genetic heterogeneity and clonal evolution in advanced papillary thyroid carcinomas and matched distant metastases." In Proceedings: AACR Annual Meeting 2019; March 29-April 3, 2019; Atlanta, GA. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1538-7445.am2019-2770.

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Liu, Fabao, Xingli Jia, Dang Wang, and Ao Du. "Analysis on the Spatio-Temporal Heterogeneity of the Regional Ecosystem Services Value in the Process of Road Networking." In 20th COTA International Conference of Transportation Professionals. American Society of Civil Engineers, 2020. http://dx.doi.org/10.1061/9780784482933.287.

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