Gerald Woo

According to our database, Gerald Woo authored at least 13 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts.

Xu Liu, Juncheng Liu, Gerald Woo, Taha Aksu, Yuxuan Liang, Roger Zimmermann, Chenghao Liu, Silvio Savarese, Caiming Xiong, Doyen Sahoo

CoRR, 2024

GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation.

Taha Aksu, Gerald Woo, Juncheng Liu, Xu Liu, Chenghao Liu, Silvio Savarese, Caiming Xiong, Doyen Sahoo

CoRR, 2024

UniTST: Effectively Modeling Inter-Series and Intra-Series Dependencies for Multivariate Time Series Forecasting.

Juncheng Liu, Chenghao Liu, Gerald Woo, Yiwei Wang, Bryan Hooi, Caiming Xiong, Doyen Sahoo

CoRR, 2024

Unified Training of Universal Time Series Forecasting Transformers.

Gerald Woo, Chenghao Liu, Akshat Kumar, Caiming Xiong, Silvio Savarese, Doyen Sahoo

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Merlion: End-to-End Machine Learning for Time Series.

Aadyot Bhatnagar, Paul Kassianik, Chenghao Liu, Tian Lan, Wenzhuo Yang, Rowan Cassius, Doyen Sahoo, Devansh Arpit, Sri Subramanian, Gerald Woo, Amrita Saha, Arun Kumar Jagota, Gokulakrishnan Gopalakrishnan, Manpreet Singh, K. C. Krithika, Sukumar Maddineni, Dae-ki Cho, Bo Zong, Yingbo Zhou, Caiming Xiong, Silvio Savarese, Steven C. H. Hoi, Huan Wang

J. Mach. Learn. Res., 2023

Pushing the Limits of Pre-training for Time Series Forecasting in the CloudOps Domain.

Gerald Woo, Chenghao Liu, Akshat Kumar, Doyen Sahoo

CoRR, 2023

AI for IT Operations (AIOps) on Cloud Platforms: Reviews, Opportunities and Challenges.

Qian Cheng, Doyen Sahoo, Amrita Saha, Wenzhuo Yang, Chenghao Liu, Gerald Woo, Manpreet Singh, Silvio Savarese, Steven C. H. Hoi

CoRR, 2023

Learning Deep Time-index Models for Time Series Forecasting.

Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven C. H. Hoi

Proceedings of the International Conference on Machine Learning, 2023

2022

Model Agnostic Defence Against Backdoor Attacks in Machine Learning.

Sakshi Udeshi, Shanshan Peng, Gerald Woo, Lionell Loh, Louth Rawshan, Sudipta Chattopadhyay

IEEE Trans. Reliab., 2022

DeepTIMe: Deep Time-Index Meta-Learning for Non-Stationary Time-Series Forecasting.

Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven C. H. Hoi

CoRR, 2022

ETSformer: Exponential Smoothing Transformers for Time-series Forecasting.

Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven C. H. Hoi

CoRR, 2022

CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting.

Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven C. H. Hoi

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Merlion: A Machine Learning Library for Time Series.

Aadyot Bhatnagar, Paul Kassianik, Chenghao Liu, Tian Lan, Wenzhuo Yang, Rowan Cassius, Doyen Sahoo, Devansh Arpit, Sri Subramanian, Gerald Woo, Amrita Saha, Arun Kumar Jagota, Gokulakrishnan Gopalakrishnan, Manpreet Singh, K. C. Krithika, Sukumar Maddineni, Dae-ki Cho, Bo Zong, Yingbo Zhou, Caiming Xiong, Silvio Savarese, Steven C. H. Hoi, Huan Wang

CoRR, 2021