YaGuang Li
YaGuang Li
Google DeepMind
Verified email at - Homepage
Cited by
Cited by
Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting
Y Li, R Yu, C Shahabi, Y Liu
International Conference on Learning Representations (ICLR), 2018
Lamda: Language models for dialog applications
R Thoppilan, D De Freitas, J Hall, N Shazeer, A Kulshreshtha, HT Cheng, ...
arXiv preprint arXiv:2201.08239, 2022
Spatiotemporal Multi-Graph Convolution Network for Ride-hailing Demand Forecasting
Y Li*, X Geng*, L Wang, L Zhang, Q Yang, J Ye, Y Liu
The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), 2019
Palm 2 technical report
R Anil, AM Dai, O Firat, M Johnson, D Lepikhin, A Passos, S Shakeri, ...
arXiv preprint arXiv:2305.10403, 2023
Deep Learning: A Generic Approach for Extreme Condition Traffic Forecasting
Y Li*, R Yu*, C Shahabi, U Demiryurek, Y Liu
Proceedings of the 2017 SIAM International Conference on Data Mining (SDM), 2017
Gemini: A family of highly capable multimodal models
G Team
Technical report, Google, 12 2023. URL https://storage. googleapis. com …, 2023
Multi-task representation learning for travel time estimation
Y Li, K Fu, Z Wang, C Shahabi, J Ye, Y Liu
Proceedings of the 24th ACM SIGKDD international conference on knowledge …, 2018
Price-aware Real-time Ride-sharing at Scale-An Auction-based Approach
M Asghari, D Deng, C Shahabi, U Demiryurek, Y Li
International Conference on Advances in Geographic Information Systems, 2016, 2016
Exploiting Spatiotemporal Patterns for Accurate Air Quality Forecasting using Deep Learning
Y Lin, N Mago, Y Gao, Y Li, YY Chiang, C Shahabi, JL Ambite
Diffusion convolutional recurrent neural network: Data-driven traffic forecasting. arXiv 2017
Y Li, R Yu, C Shahabi, Y Liu
arXiv preprint arXiv:1707.01926, 2017
Graph convolutional recurrent neural network: Data-driven traffic forecasting
Y Li, R Yu, C Shahabi, Y Liu
arXiv preprint arXiv:1707.01926 7 (8), 2017
A brief overview of machine learning methods for short-term traffic forecasting and future directions
Y Li, C Shahabi
Sigspatial Special 10 (1), 3-9, 2018
Effective map-matching on the most simplified road network
K Liu, Y Li, F He, J Xu, Z Ding
Proceedings of the 20th International Conference on Advances in Geographic …, 2012
Predicting Origin-Destination Flow via Multi-Perspective Graph Convolutional Network
H Shi, Q Yao, Q Guo, Y Li, L Zhang, J Ye, Y Li, Y Liu
IEEE International Conference on Data Engineering (ICDE), 2020
CoSTCo: A Neural Tensor Completion Model for Sparse Tensors
H Liu, Y Li, M Tsang, Y Liu
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2019
Network-Matched Trajectory-Based Moving-Object Database: Models and Applications
Z Ding, B Yang, RH Guting, Y Li
IEEE Transactions on Intelligent Transportation Systems 16, 1918-1928, 2015
Hyperprompt: Prompt-based task-conditioning of transformers
Y He, S Zheng, Y Tay, J Gupta, Y Du, V Aribandi, Z Zhao, YG Li, Z Chen, ...
International conference on machine learning, 8678-8690, 2022
DETECT: Deep Trajectory Clustering for Mobility-Behavior Analysis
M Yue, Y Li, H Yang, R Ahuja, YY Chiang, C Shahabi
IEEE International Conference on Big Data, (IEEE Bigdata), 2019
Compressing large scale urban trajectory data
K Liu, Y Li, J Dai, S Shang, K Zheng
Proceedings of the Fourth International Workshop on Cloud Data and Platforms …, 2014
Towards fast and accurate solutions to vehicle routing in a large-scale and dynamic environment
Y Li, D Deng, U Demiryurek, C Shahabi, S Ravada
Advances in Spatial and Temporal Databases: 14th International Symposium …, 2015
The system can't perform the operation now. Try again later.
Articles 1–20