Yuyang (Bernie) Wang
Yuyang (Bernie) Wang
Principal Scientist, AWS AI Labs
Потвърден имейл адрес: mit.edu - Начална страница
Deep state space models for time series forecasting
SS Rangapuram, MW Seeger, J Gasthaus, L Stella, Y Wang, ...
Advances in neural information processing systems 31, 2018
Gluonts: Probabilistic and neural time series modeling in python
A Alexandrov, K Benidis, M Bohlke-Schneider, V Flunkert, J Gasthaus, ...
The Journal of Machine Learning Research 21 (1), 4629-4634, 2020
Deep Factors for Forecasting
Y Wang, A Smola, DC Maddix, J Gasthaus, D Foster, T Januschowski
ICML 2019, arXiv preprint arXiv:1905.12417, 2019
Criteria for classifying forecasting methods
T Januschowski, J Gasthaus, Y Wang, D Salinas, V Flunkert, ...
International Journal of Forecasting 36 (1), 167-177, 2020
Probabilistic forecasting with spline quantile function RNNs
J Gasthaus, K Benidis, Y Wang, SS Rangapuram, D Salinas, V Flunkert, ...
The 22nd international conference on artificial intelligence and statistics …, 2019
Deep learning for time series forecasting: Tutorial and literature survey
K Benidis, SS Rangapuram, V Flunkert, Y Wang, D Maddix, C Turkmen, ...
ACM Computing Surveys 55 (6), 1-36, 2022
Probabilistic Demand Forecasting at Scale
YW Joos-Hendrik Boese, Valentin Flunkert, Jan Gasthaus, Tim Januschowski ...
Proceedings of the VLDB Endowment 10 (12), 1694-1705, 2017
Generalization Bounds for Online Learning Algorithms with Pairwise Loss Functions
Y Wang, R Khardon, D Pechyony, R Jones
Annual Conference on Learning Theory, 2012
Elastic Machine Learning Algorithms in Amazon SageMaker
E Liberty, Z Karnin, B Xiang, L Rouesnel, B Coskun, R Nallapati, ...
SIGMOD, 2020
Random Matrix Theory and Its Innovative Applications
A Edelman, Y Wang
Advances in Applied Mathematics, Modeling, and Computational Science, 91-116, 2012
Forecasting big time series: old and new
C Faloutsos, J Gasthaus, T Januschowski, Y Wang
Proceedings of the VLDB Endowment 11 (12), 2102-2105, 2018
Nonparametric Bayesian estimation of periodic light curves
Y Wang, R Khardon, P Protopapas
The Astrophysical Journal 756 (1), 67, 2012
Sparse Variational Inference for Generalized Gaussian Process Models
R Sheth, Y Wang, R Khardon
International Conference on Machine Learning, 2015
Deep factors with gaussian processes for forecasting
DC Maddix, Y Wang, A Smola
NeurIPS Workshop on Bayesian Deep Learning, 2018
Bridging physics-based and data-driven modeling for learning dynamical systems
R Wang, D Maddix, C Faloutsos, Y Wang, R Yu
Learning for Dynamics and Control, 385-398, 2021
Forecasting big time series: Theory and practice
C Faloutsos, V Flunkert, J Gasthaus, T Januschowski, Y Wang
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
Forecasting with trees
T Januschowski, Y Wang, K Torkkola, T Erkkilä, H Hasson, J Gasthaus
International Journal of Forecasting 38 (4), 1473-1481, 2022
FastPoint: Scalable Deep Point Processes
AC Türkmen, Y Wang, AJ Smola
ECML, 2019
Forecasting intermittent and sparse time series: A unified probabilistic framework via deep renewal processes
AC Türkmen, T Januschowski, Y Wang, AT Cemgil
Plos one 16 (11), e0259764, 2021
Approximate bayesian inference in linear state space models for intermittent demand forecasting at scale
M Seeger, S Rangapuram, Y Wang, D Salinas, J Gasthaus, ...
arXiv preprint arXiv:1709.07638, 2017
Системата не може да изпълни операцията сега. Опитайте отново по-късно.
Статии 1–20