Yuyang Wang
Orcid: 0000-0002-0291-7184Affiliations:
- Amazon Web Services, AWS, AI Labs, Palo Alto, CA, USA
- Amazon Research, Amazon Development Center, Berlin, Germany
According to our database1,
Yuyang Wang
authored at least 51 papers
between 2017 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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Online presence:
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on web.mit.edu
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on orcid.org
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Bibliography
2024
Comparing and Contrasting Deep Learning Weather Prediction Backbones on Navier-Stokes and Atmospheric Dynamics.
CoRR, 2024
CoRR, 2024
Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs.
CoRR, 2024
CoRR, 2024
2023
ACM Comput. Surv., 2023
Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Automated Machine Learning, 2023
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
2022
CoRR, 2022
Modeling Advection on Directed Graphs using Matérn Gaussian Processes for Traffic Flow.
CoRR, 2022
On the detrimental effect of invariances in the likelihood for variational inference.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
8th SIGKDD International Workshop on Mining and Learning from Time Series - Deep Forecasting: Models, Interpretability, and Applications.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
CoRR, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
GOPHER: Categorical probabilistic forecasting with graph structure via local continuous-time dynamics.
Proceedings of the I (Still) Can't Believe It's Not Better! Workshop at NeurIPS 2021, 2021
2020
J. Mach. Learn. Res., 2020
Proceedings of the Companion of The 2020 Web Conference 2020, 2020
Proceedings of the 2020 International Conference on Management of Data, 2020
2019
Proceedings of the 2019 International Conference on Management of Data, 2019
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
2017
Approximate Bayesian Inference in Linear State Space Models for Intermittent Demand Forecasting at Scale.
CoRR, 2017