Rose Yu
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Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting
Y Li, R Yu, C Shahabi, Y Liu
International Conference on Learning Representations (ICLR), 2018
Deep learning: A generic approach for extreme condition traffic forecasting
R Yu, Y Li, C Shahabi, U Demiryurek, Y Liu
Proceedings of the 2017 SIAM international Conference on Data Mining, 777-785, 2017
GLAD: group anomaly detection in social media analysis
R Yu, X He, Y Liu
ACM Transactions on Knowledge Discovery from Data (TKDD) 10 (2), 18, 2015
Fast Multivariate Spatio-Temporal Analysis via Low-Rank Tensor Learning
R Yu, MT Bahadori, Y Liu
Advances in Neural Information Processing Systems, 3491-3499, 2014
Latent Space Model for Road Networks to Predict Time-Varying Traffic
D Deng, C Shahabi, U Demiryurek, L Zhu, R Yu, Y Liu
Proceedings of the 22nd ACM SIGKDD international conference on Knowledge …, 2016
Long-term forecasting using higher order tensor RNNs
R Yu, S Zheng, A Anandkumar, Y Yue
arXiv preprint arXiv:1711.00073, 2017
Neural lander: Stable drone landing control using learned dynamics
G Shi, X Shi, M O’Connell, R Yu, K Azizzadenesheli, A Anandkumar, ...
2019 International Conference on Robotics and Automation (ICRA), 9784-9790, 2019
A feasible nonconvex relaxation approach to feature selection.
C Gao, N Wang, QR Yu, Z Zhang
AAAI, 356-361, 2011
Accelerated online low rank tensor learning for multivariate spatiotemporal streams
R Yu, D Cheng, Y Liu
International Conference on Machine Learning, 238-247, 2015
Learning from Multiway Data: Simple and Efficient Tensor Regression
R Yu, Y Liu
Proceedings of the 33rd International Conference on Machine Learning (ICML-16), 2016
A Survey on Social Media Anomaly Detection
R Yu, H Qiu, Z Wen, CY Lin, Y Liu
arXiv preprint arXiv:1601.01102, 2015
Understanding the representation power of graph neural networks in learning graph topology
N Dehmamy, AL Barabási, R Yu
Advances in Neural Information Processing Systems, 15413-15423, 2019
Socratic learning: Augmenting generative models to incorporate latent subsets in training data
P Varma, B He, D Iter, P Xu, R Yu, C De Sa, C Ré
arXiv preprint arXiv:1610.08123, 2016
Tensor Regression Meets Gaussian Processes
R Yu, G Li, Y Liu
21st International Conference on Artificial Intelligence and Statistics …, 2018
Towards physics-informed deep learning for turbulent flow prediction
R Wang, K Kashinath, M Mustafa, A Albert, R Yu
Proceedings of the 26th ACM SIGKDD international conference on Knowledge …, 2020
Naomi: Non-autoregressive multiresolution sequence imputation
Y Liu, R Yu, S Zheng, E Zhan, Y Yue
Advances in Neural Information Processing Systems, 11238-11248, 2019
Latent space model for road networks to predict time-varying traffic
U Demiryurek, D Deng, C Shahabi, L Zhu, R Yu, Y Liu
US Patent App. 16/326,138, 2019
Geographic segmentation via latent poisson factor model
R Yu, A Gelfand, S Rajan, C Shahabi, Y Liu
Proceedings of the Ninth ACM International Conference on Web Search and Data …, 2016
Incorporating Symmetry into Deep Dynamics Models for Improved Generalization
R Wang, R Walters, R Yu
arXiv preprint arXiv:2002.03061, 2020
Efficient spatio-temporal sampling via low-rank tensor sketching
R Yu, S Purushotham, Y Liu
Proc. Time Series Workshop at Conf. Neural Info. Process. Syst.(NIPS), 5, 2015
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