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Foundation models have revolutionized artificial intelligence, setting new benchmarks in performance and enabling transformative capabilities across a wide range of vision and language tasks.
The coupled model intercomparison project (cmip)
Gerald A Meehl, George J Boer, Curt Covey, Mojib Latif, and Ronald J Stouffer · 2000
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Spatio-temporal data mining for climate data: Advances, challenges, and opportunities
James H Faghmous and Vipin Kumar · 2014
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Convolutional lstm network: A machine learning approach for precipitation nowcasting
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Attention is all you need
A Vaswani · 2017
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Spatio-temporal graph convolutional networks: A deep learning framework for traffic forecasting
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Julie Yixuan Zhu, Chao Zhang, Huichu Zhang, Shi Zhi, Victor OK Li, Jiawei Han, and Yu Zheng · 2017
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Jacob Devlin · 2018
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Deepstcl: A deep spatio-temporal convlstm for travel demand prediction
Dongjie Wang, Yan Yang, and Shangming Ning · 2018
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Predicting the spatio-temporal evolution of chronic diseases in population with human mobility data
Yingzi Wang, Xiao Zhou, Cecilia Mascolo, Anastasios Noulas, Xing Xie, and Qi Liu · 2018
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Spatio-temporal prediction of crop disease severity for agricultural emergency management based on recurrent neural networks
Wei Xu, Qili Wang, and Runyu Chen · 2018
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Bi-directional convlstm u-net with densley connected convolutions
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Rui Chen, Xiang Wang, Weimin Zhang, Xiaoyu Zhu, Aiping Li, and Chao Yang · 2019
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Urban traffic prediction from spatio-temporal data using deep meta learning
Zheyi Pan, Yuxuan Liang, Weifeng Wang, Yong Yu, Yu Zheng, and Junbo Zhang · 2019
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A novel spatiotemporal convolutional long short-term neural network for air pollution prediction
Congcong Wen, Shufu Liu, Xiaojing Yao, Ling Peng, Xiang Li, Yuan Hu, and Tianhe Chi · 2019
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A novel framework for spatio-temporal prediction of environmental data using deep learning
Federico Amato, Fabian Guignard, Sylvain Robert, and Mikhail Kanevski · 2020
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Toon Bogaerts, Antonio D Masegosa, Juan S Angarita-Zapata, Enrique Onieva, and Peter Hellinckx · 2020
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Amol Kapoor, Xue Ben, Luyang Liu, Bryan Perozzi, Matt Barnes, Martin Blais, and Shawn O’Banion · 2020
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Self-attention convlstm for spatiotemporal prediction
Zhihui Lin, Maomao Li, Zhuobin Zheng, Yangyang Cheng, and Chun Yuan · 2020
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Social-stgcnn: A social spatio-temporal graph convolutional neural network for human trajectory prediction
Abduallah Mohamed, Kun Qian, Mohamed Elhoseiny, and Christian Claudel · 2020
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Crop yield prediction using multitemporal uav data and spatio-temporal deep learning models
Petteri Nevavuori, Nathaniel Narra, Petri Linna, and Tarmo Lipping · 2020
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A survey on modern deep neural network for traffic prediction: Trends, methods and challenges
David Alexander Tedjopurnomo, Zhifeng Bao, Baihua Zheng, Farhana Murtaza Choudhury, and Alex Kai Qin · 2020
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Urban flow prediction from spatiotemporal data using machine learning: A survey
Peng Xie, Tianrui Li, Jia Liu, Shengdong Du, Xin Yang, and Junbo Zhang · 2020
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Spatio-temporal graph transformer networks for pedestrian trajectory prediction
Cunjun Yu, Xiao Ma, Jiawei Ren, Haiyu Zhao, and Shuai Yi · 2020
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Spatio-temporal graph structure learning for traffic forecasting
Qi Zhang, Jianlong Chang, Gaofeng Meng, Shiming Xiang, and Chunhong Pan · 2020
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Regional air quality forecasting using spatiotemporal deep learning
S Abirami and P Chitra · 2021
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A spatio-temporal transformer for 3d human motion prediction
Emre Aksan, Manuel Kaufmann, Peng Cao, and Otmar Hilliges · 2021
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Causalgnn: Causal-based graph neural networks for spatio-temporal epidemic forecasting
Lijing Wang, Aniruddha Adiga, Jiangzhuo Chen, Adam Sadilek, Srinivasan Venkatramanan, and Madhav Marathe · 2022
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Deep learning of spatiotemporal patterns for urban mobility prediction using big data
Yun Wang, Faiz Currim, and Sudha Ram · 2022
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Improving yield prediction based on spatio-temporal deep learning approaches for winter wheat: A case study in jiangsu province, china
Peipei Chen, Yue Li, Xiaojun Liu, Yongchao Tian, Yan Zhu, Weixing Cao, and Qiang Cao · 2023
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Spatio-temporal graph neural networks for predictive learning in urban computing: A survey
Guangyin Jin, Yuxuan Liang, Yuchen Fang, Zezhi Shao, Jincai Huang, Junbo Zhang, and Yu Zheng · 2023
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Time-llm: Time series forecasting by reprogramming large language models
Ming Jin, Shiyu Wang, Lintao Ma, Zhixuan Chu, James Y Zhang, Xiaoming Shi, Pin-Yu Chen, Yuxuan Liang, Yuan-Fang Li, Shirui Pan, et al · 2023
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Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al · 2021
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Stconvs2s: Spatiotemporal convolutional sequence to sequence network for weather forecasting
Rafaela Castro, Yania M Souto, Eduardo Ogasawara, Fabio Porto, and Eduardo Bezerra · 2021
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Long-range transformers for dynamic spatiotemporal forecasting
Jake Grigsby, Zhe Wang, Nam Nguyen, and Yanjun Qi · 2021
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Sub-seasonal climate forecasting via machine learning: Challenges, analysis, and advances
Sijie He, Xinyan Li, Timothy DelSole, Pradeep Ravikumar, and Arindam Banerjee · 2021
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Scaling up visual and vision-language representation learning with noisy text supervision
Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc Le, Yun-Hsuan Sung, Zhen Li, and Tom Duerig · 2021
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Spatio-temporal prediction of the covid-19 pandemic in us counties: modeling with a deep lstm neural network
Behnam Nikparvar, Md Mokhlesur Rahman, Faizeh Hatami, and Jean-Claude Thill · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Self-regulating prompts: Foundational model adaptation without forgetting
Muhammad Uzair Khattak, Syed Talal Wasim, Muzammal Naseer, Salman Khan, Ming-Hsuan Yang, and Fahad Shahbaz Khan · 2023
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Segment anything
Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C Berg, Wan-Yen Lo, et al · 2023
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Histgnn: Hierarchical spatio-temporal graph neural network for weather forecasting
Minbo Ma, Peng Xie, Fei Teng, Bin Wang, Shenggong Ji, Junbo Zhang, and Tianrui Li · 2023
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W-mae: Pre-trained weather model with masked autoencoder for multi-variable weather forecasting
Xin Man, Chenghong Zhang, Jin Feng, Changyu Li, and Jie Shao · 2023
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Climax: A foundation model for weather and climate
Tung Nguyen, Johannes Brandstetter, Ashish Kapoor, Jayesh K Gupta, and Aditya Grover · 2023
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Lag-llama: Towards foundation models for time series forecasting
Kashif Rasul, Arjun Ashok, Andrew Robert Williams, Arian Khorasani, George Adamopoulos, Rishika Bhagwatkar, Marin Biloš, Hena Ghonia, Nadhir Hassen, Anderson Schneider, et al · 2023
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Spatio-temporal graph neural networks: A survey
Zahraa Al Sahili and Mariette Awad · 2023
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al · 2023
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Spatio-temporal graph learning for epidemic prediction
Shuo Yu, Feng Xia, Shihao Li, Mingliang Hou, and Quan Z Sheng · 2023
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Generative causal interpretation model for spatio-temporal representation learning
Yu Zhao, Pan Deng, Junting Liu, Xiaofeng Jia, and Jianwei Zhang · 2023
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Urbangpt: Spatio-temporal large language models
Zhonghang Li, Lianghao Xia, Jiabin Tang, Yong Xu, Lei Shi, Long Xia, Dawei Yin, and Chao Huang · 2024
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Opencity: Open spatio-temporal foundation models for traffic prediction
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Foundation models for time series analysis: A tutorial and survey
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Few-shot adaptation of multi-modal foundation models: A survey
Fan Liu, Tianshu Zhang, Wenwen Dai, Chuanyi Zhang, Wenwen Cai, Xiaocong Zhou, and Delong Chen · 2024
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Lsttn: A long-short term transformer-based spatiotemporal neural network for traffic flow forecasting
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Artificial intelligence for climate prediction of extremes: State of the art, challenges, and future perspectives
Stefano Materia, Lluís Palma García, Chiem van Straaten, Sungmin O, Antonios Mamalakis, Leone Cavicchia, Dim Coumou, Paolo de Luca, Marlene Kretschmer, and Markus Donat · 2024
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Unified training of universal time series forecasting transformers
Gerald Woo, Chenghao Liu, Akshat Kumar, Caiming Xiong, Silvio Savarese, and Doyen Sahoo · 2024
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Deciphering spatio-temporal graph forecasting: A causal lens and treatment
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Unist: A prompt-empowered universal model for urban spatio-temporal prediction
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A foundation model for unified urban spatio-temporal flow prediction
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Urbandit: A foundation model for open-world urban spatio-temporal learning
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
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