RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies

3 February 2024

Hao Cheng

Qingsong Wen

Yang Liu

Liang Sun

OOD

AI4TS

ArXiv (abs)PDF HTML Github (20★)

Papers citing "RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies"

20 / 20 papers shown

Title
Robust Learning of Deep Time Series Anomaly Detection Models with Contaminated Training Data Wenkai Li Cheng Feng Tingling Chen Jun Zhu AAML AI4TS 66 6 0 03 Aug 2022
Trimmed Maximum Likelihood Estimation for Robust Learning in Generalized Linear Models Pranjal Awasthi Abhimanyu Das Weihao Kong Rajat Sen 58 6 0 09 Jun 2022
Resilient Neural Forecasting Systems Michael Bohlke-Schneider Shubham Kapoor Tim Januschowski 15 10 0 16 Mar 2022
Robust Probabilistic Time Series Forecasting Taeho Yoon Youngsuk Park Ernest K. Ryu Yuyang Wang AAML AI4TS 51 18 0 24 Feb 2022
FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting Tian Zhou Ziqing Ma Qingsong Wen Xue Wang Liang Sun Rong Jin AI4TS 248 1,435 0 30 Jan 2022
Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series Yinjun Wu Jingchao Ni Wei Cheng Bo Zong Dongjin Song Zhengzhang Chen Yanchi Liu Xuchao Zhang Haifeng Chen S. Davidson AI4TS 66 50 0 03 Mar 2021
A Second-Order Approach to Learning with Instance-Dependent Label Noise Zhaowei Zhu Tongliang Liu Yang Liu NoLa 69 129 0 22 Dec 2020
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach Hao Cheng Zhaowei Zhu Xingyu Li Yifei Gong Xing Sun Yang Liu NoLa 68 209 0 05 Oct 2020
Learning from Noisy Labels with Deep Neural Networks: A Survey Hwanjun Song Minseok Kim Dongmin Park Yooju Shin Jae-Gil Lee NoLa 111 992 0 16 Jul 2020
Normalized Loss Functions for Deep Learning with Noisy Labels Xingjun Ma Hanxun Huang Yisen Wang Simone Romano S. Erfani James Bailey NoLa 73 445 0 24 Jun 2020
Learning under Concept Drift: A Review Jie Lu Anjin Liu Fan Dong Feng Gu João Gama Guangquan Zhang AI4TS 65 1,290 0 13 Apr 2020
DivideMix: Learning with Noisy Labels as Semi-supervised Learning Junnan Li R. Socher Guosheng Lin NoLa 107 1,034 0 18 Feb 2020
A review on outlier/anomaly detection in time series data Ane Blázquez-García Angel Conde U. Mori Jose A. Lozano AI4TS 64 735 0 11 Feb 2020
Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates Yang Liu Hongyi Guo NoLa 56 241 0 08 Oct 2019
High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes David Salinas Michael Bohlke-Schneider Laurent Callot Roberto Medico Jan Gasthaus AI4TS 71 229 0 07 Oct 2019
Robust Loss Functions under Label Noise for Deep Neural Networks Aritra Ghosh Himanshu Kumar P. Sastry NoLa OOD 78 959 0 27 Dec 2017
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels Lu Jiang Zhengyuan Zhou Thomas Leung Li Li Li Fei-Fei NoLa 117 1,456 0 14 Dec 2017
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks David Salinas Valentin Flunkert Jan Gasthaus AI4TS UQCV BDL 85 2,123 0 13 Apr 2017
Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks Guokun Lai Wei-Cheng Chang Yiming Yang Hanxiao Liu BDL AI4TS 108 2,024 0 21 Mar 2017
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,121 0 20 Dec 2014