Yuyang Wang

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 25

Top Topics

Diffusion Model

Dimensional Data

International Workshop

Variational Inference

Top Venues

Publications

Abdul Fatir Ansari, Lorenzo Stella, Ali Caner Türkmen, Xiyuan Zhang, Pedro Mercado, Huibin Shen, Oleksandr Shchur, Syama Sundar Rangapuram, Sebastian Pineda-Arango, Shubham Kapoor, Jasper Zschiegner, Danielle C. Maddix, Michael W. Mahoney, Kari Torkkola, Andrew Gordon Wilson, Michael Bohlke-Schneider, Yuyang Wang
Chronos: Learning the Language of Time Series. CoRR (2024)
S. Chandra Mouli, Danielle C. Maddix, Shima Alizadeh, Gaurav Gupta, Andrew Stuart, Michael W. Mahoney, Yuyang Wang
Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs. CoRR (2024)
Matthias Karlbauer, Danielle C. Maddix, Abdul Fatir Ansari, Boran Han, Gaurav Gupta, Yuyang Wang, Andrew Stuart, Michael W. Mahoney
Comparing and Contrasting Deep Learning Weather Prediction Backbones on Navier-Stokes and Atmospheric Dynamics. CoRR (2024)
Hilaf Hasson, Danielle C. Maddix, Yuyang Wang, Gaurav Gupta, Youngsuk Park
Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting. CoRR (2023)
Syama Sundar Rangapuram, Jan Gasthaus, Lorenzo Stella, Valentin Flunkert, David Salinas, Yuyang Wang, Tim Januschowski
Deep Non-Parametric Time Series Forecaster. CoRR (2023)
Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle C. Maddix, Yi Zhu, Mu Li, Yuyang Wang
PreDiff: Precipitation Nowcasting with Latent Diffusion Models. CoRR (2023)
Charles Marx, Youngsuk Park, Hilaf Hasson, Yuyang Wang, Stefano Ermon, Luke Huan
But Are You Sure? An Uncertainty-Aware Perspective on Explainable AI. AISTATS (2023)
Syama Sundar Rangapuram, Shubham Kapoor, Rajbir-Singh Nirwan, Pedro Mercado, Tim Januschowski, Yuyang Wang, Michael Bohlke-Schneider
Coherent Probabilistic Forecasting of Temporal Hierarchies. AISTATS (2023)
Konstantinos Benidis, Syama Sundar Rangapuram, Valentin Flunkert, Yuyang Wang, Danielle C. Maddix, Ali Caner Türkmen, Jan Gasthaus, Michael Bohlke-Schneider, David Salinas, Lorenzo Stella, François-Xavier Aubet, Laurent Callot, Tim Januschowski
Deep Learning for Time Series Forecasting: Tutorial and Literature Survey. ACM Comput. Surv. 55 (6) (2023)
Marcel Kollovieh, Abdul Fatir Ansari, Michael Bohlke-Schneider, Jasper Zschiegner, Hao Wang, Yuyang Wang
Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting. NeurIPS (2023)
Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle C. Maddix, Yi Zhu, Mu Li, Yuyang Wang
PreDiff: Precipitation Nowcasting with Latent Diffusion Models. NeurIPS (2023)
Arun Jambulapati, Hilaf Hasson, Youngsuk Park, Yuyang Wang
Testing Causality for High Dimensional Data. CoRR (2023)
Marcel Kollovieh, Abdul Fatir Ansari, Michael Bohlke-Schneider, Jasper Zschiegner, Hao Wang, Yuyang Wang
Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting. CoRR (2023)
Richard Kurle, Ralf Herbrich, Tim Januschowski, Yuyang Wang, Jan Gasthaus
On the detrimental effect of invariances in the likelihood for variational inference. CoRR (2022)
Xiyuan Zhang, Xiaoyong Jin, Karthick Gopalswamy, Gaurav Gupta, Youngsuk Park, Xingjian Shi, Hao Wang, Danielle C. Maddix, Yuyang Wang
First De-Trend then Attend: Rethinking Attention for Time-Series Forecasting. CoRR (2022)
Sanjay Purushotham, Jun Huan, Cong Shen, Dongjin Song, Yuyang Wang, Jan Gasthaus, Hilaf Hasson, Youngsuk Park, Sungyong Seo, Yuriy Nevmyvaka
8th SIGKDD International Workshop on Mining and Learning from Time Series - Deep Forecasting: Models, Interpretability, and Applications. KDD (2022)
Tim Januschowski, Jan Gasthaus, Yuyang Wang, David Salinas, Valentin Flunkert, Michael Bohlke-Schneider, Laurent Callot
Criteria for Classifying Forecasting Methods. CoRR (2022)
Youngsuk Park, Danielle C. Maddix, François-Xavier Aubet, Kelvin Kan, Jan Gasthaus, Yuyang Wang
Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting. AISTATS (2022)
Hao Wang, Yifei Ma, Hao Ding, Yuyang Wang
Context Uncertainty in Contextual Bandits with Applications to Recommender Systems. AAAI (2022)
Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Yuyang Wang, Mu Li, Dit-Yan Yeung
Earthformer: Exploring Space-Time Transformers for Earth System Forecasting. NeurIPS (2022)
Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Yuyang Wang, Mu Li, Dit-Yan Yeung
Earthformer: Exploring Space-Time Transformers for Earth System Forecasting. CoRR (2022)
Xiaoyong Jin, Youngsuk Park, Danielle C. Maddix, Hao Wang, Yuyang Wang
Domain Adaptation for Time Series Forecasting via Attention Sharing. ICML (2022)
Richard Kurle, Ralf Herbrich, Tim Januschowski, Yuyang Wang, Jan Gasthaus
On the detrimental effect of invariances in the likelihood for variational inference. NeurIPS (2022)
Taeho Yoon, Youngsuk Park, Ernest K. Ryu, Yuyang Wang
Robust Probabilistic Time Series Forecasting. AISTATS (2022)
Ke Alexander Wang, Danielle C. Maddix, Yuyang Wang
GOPHER: Categorical probabilistic forecasting with graph structure via local continuous-time dynamics. ICBINB@NeurIPS (2021)