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Koopa: Learning Non-stationary Time Series Dynamics with Koopman
  Predictors
v1v2 (latest)

Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors

30 May 2023
Yong Liu
Chenyu Li
Jianmin Wang
Mingsheng Long
    AI4TS
ArXiv (abs)PDFHTML

Papers citing "Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors"

43 / 43 papers shown
Title
Non-stationary Diffusion For Probabilistic Time Series Forecasting
Non-stationary Diffusion For Probabilistic Time Series Forecasting
Weiwei Ye
Zhuopeng Xu
Ning Gui
DiffM
125
0
0
07 May 2025
FreCT: Frequency-augmented Convolutional Transformer for Robust Time Series Anomaly Detection
FreCT: Frequency-augmented Convolutional Transformer for Robust Time Series Anomaly Detection
Wenxin Zhang
Ding Xu
Guangzhen Yao
Xiaojian Lin
Renxiang Guan
Chengze Du
Renda Han
Xi Xuan
Cuicui Luo
AI4TS
157
0
0
02 May 2025
Temporal Gaussian Copula For Clinical Multivariate Time Series Data Imputation
Temporal Gaussian Copula For Clinical Multivariate Time Series Data Imputation
Ye Su
Hezhe Qiao
Di Wu
Yuwen Chen
Lin Chen
69
0
0
03 Apr 2025
On the Surprising Effectiveness of Spectrum Clipping in Learning Stable Linear Dynamics
On the Surprising Effectiveness of Spectrum Clipping in Learning Stable Linear Dynamics
Hanyao Guo
Yunhai Han
Harish Ravichandar
130
0
0
02 Dec 2024
LiNo: Advancing Recursive Residual Decomposition of Linear and Nonlinear Patterns for Robust Time Series Forecasting
LiNo: Advancing Recursive Residual Decomposition of Linear and Nonlinear Patterns for Robust Time Series Forecasting
Guoqi Yu
Yaoming Li
Xiaoyu Guo
Dayu Wang
Zirui Liu
Shujun Wang
Tong Yang
AI4TS
466
0
0
22 Oct 2024
TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis
TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis
Shiyu Wang
Jiawei Li
Xiaoming Shi
Zhou Ye
Baichuan Mo
Wenze Lin
Shengtong Ju
Zhixuan Chu
Ming Jin
AI4TS
110
18
0
21 Oct 2024
Automated Detection of Defects on Metal Surfaces using Vision
  Transformers
Automated Detection of Defects on Metal Surfaces using Vision Transformers
Toqa Alaa
Mostafa Kotb
Arwa Zakaria
Mariam Diab
Walid Gomaa
151
1
0
06 Oct 2024
Online Control-Informed Learning
Online Control-Informed Learning
Zihao Liang
Tianyu Zhou
Zehui Lu
Shaoshuai Mou
102
1
0
04 Oct 2024
Deep Koopman-layered Model with Universal Property Based on Toeplitz Matrices
Deep Koopman-layered Model with Universal Property Based on Toeplitz Matrices
Yuka Hashimoto
Tomoharu Iwata
74
0
0
03 Oct 2024
FTS: A Framework to Find a Faithful TimeSieve
FTS: A Framework to Find a Faithful TimeSieve
Songning Lai
Ninghui Feng
Haochen Sui
Ze Ma
Hao Wang
Zichen Song
Hang Zhao
Yutao Yue
AI4TS
153
17
0
30 May 2024
Multifactor Sequential Disentanglement via Structured Koopman
  Autoencoders
Multifactor Sequential Disentanglement via Structured Koopman Autoencoders
Nimrod Berman
Ilana D Naiman
Omri Azencot
CoGe
86
24
0
30 Mar 2023
Koopman neural operator as a mesh-free solver of non-linear partial
  differential equations
Koopman neural operator as a mesh-free solver of non-linear partial differential equations
Wei Xiong
Xiaomeng Huang
Ziyang Zhang
Ruixuan Deng
Pei Sun
Yang Tian
AI4CE
71
34
0
24 Jan 2023
A Time Series is Worth 64 Words: Long-term Forecasting with Transformers
A Time Series is Worth 64 Words: Long-term Forecasting with Transformers
Yuqi Nie
Nam H. Nguyen
Phanwadee Sinthong
Jayant Kalagnanam
AIFinAI4TS
108
1,423
0
27 Nov 2022
Koopman Neural Forecaster for Time Series with Temporal Distribution
  Shifts
Koopman Neural Forecaster for Time Series with Temporal Distribution Shifts
Rui Wang
Yihe Dong
Sercan O. Arik
Rose Yu
AI4TS
95
28
0
07 Oct 2022
TimesNet: Temporal 2D-Variation Modeling for General Time Series
  Analysis
TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis
Haixu Wu
Teng Hu
Yong Liu
Hang Zhou
Jianmin Wang
Mingsheng Long
AI4TSAIFin
148
826
0
05 Oct 2022
Less Is More: Fast Multivariate Time Series Forecasting with Light
  Sampling-oriented MLP Structures
Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures
Tianze Zhang
Yizhuo Zhang
Wei Cao
Jiang Bian
Xiaohan Yi
Shun Zheng
Jian Li
BDLAI4TS
155
171
0
04 Jul 2022
Are Transformers Effective for Time Series Forecasting?
Are Transformers Effective for Time Series Forecasting?
Ailing Zeng
Mu-Hwa Chen
L. Zhang
Qiang Xu
AI4TS
156
1,798
0
26 May 2022
Learning Fast and Slow for Online Time Series Forecasting
Learning Fast and Slow for Online Time Series Forecasting
Quang Pham
Chenghao Liu
Doyen Sahoo
Guosheng Lin
TTAAI4TS
53
35
0
23 Feb 2022
N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting
N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting
Cristian Challu
Kin G. Olivares
Boris N. Oreshkin
Federico Garza
Max Mergenthaler-Canseco
A. Dubrawski
AI4TS
125
277
0
30 Jan 2022
Autoformer: Decomposition Transformers with Auto-Correlation for
  Long-Term Series Forecasting
Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting
Haixu Wu
Jiehui Xu
Jianmin Wang
Mingsheng Long
AI4TS
113
2,320
0
24 Jun 2021
Invariance Principle Meets Information Bottleneck for
  Out-of-Distribution Generalization
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization
Kartik Ahuja
Ethan Caballero
Dinghuai Zhang
Jean-Christophe Gagnon-Audet
Yoshua Bengio
Ioannis Mitliagkas
Irina Rish
OOD
66
270
0
11 Jun 2021
Modern Koopman Theory for Dynamical Systems
Modern Koopman Theory for Dynamical Systems
Steven L. Brunton
M. Budišić
E. Kaiser
J. Nathan Kutz
AI4CE
120
420
0
24 Feb 2021
Domain Adaptation for Time Series Forecasting via Attention Sharing
Domain Adaptation for Time Series Forecasting via Attention Sharing
Xiaoyong Jin
Youngsuk Park
Danielle C. Maddix
Bernie Wang
Xifeng Yan
TTAOODAI4TS
161
78
0
13 Feb 2021
An Image is Worth 16x16 Words: Transformers for Image Recognition at
  Scale
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Alexey Dosovitskiy
Lucas Beyer
Alexander Kolesnikov
Dirk Weissenborn
Xiaohua Zhai
...
Matthias Minderer
G. Heigold
Sylvain Gelly
Jakob Uszkoreit
N. Houlsby
ViT
684
41,563
0
22 Oct 2020
Fourier Neural Operator for Parametric Partial Differential Equations
Fourier Neural Operator for Parametric Partial Differential Equations
Zong-Yi Li
Nikola B. Kovachki
Kamyar Azizzadenesheli
Burigede Liu
K. Bhattacharya
Andrew M. Stuart
Anima Anandkumar
AI4CE
516
2,456
0
18 Oct 2020
From Fourier to Koopman: Spectral Methods for Long-term Time Series
  Prediction
From Fourier to Koopman: Spectral Methods for Long-term Time Series Prediction
Henning Lange
Steven L. Brunton
N. Kutz
AI4TS
77
80
0
01 Apr 2020
Forecasting Sequential Data using Consistent Koopman Autoencoders
Forecasting Sequential Data using Consistent Koopman Autoencoders
Omri Azencot
N. Benjamin Erichson
Vanessa Lin
Michael W. Mahoney
AI4TSAI4CE
192
152
0
04 Mar 2020
Reformer: The Efficient Transformer
Reformer: The Efficient Transformer
Nikita Kitaev
Lukasz Kaiser
Anselm Levskaya
VLM
209
2,335
0
13 Jan 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke
Sam Gross
Francisco Massa
Adam Lerer
James Bradbury
...
Sasank Chilamkurthy
Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
ODL
568
42,677
0
03 Dec 2019
N-BEATS: Neural basis expansion analysis for interpretable time series
  forecasting
N-BEATS: Neural basis expansion analysis for interpretable time series forecasting
Boris N. Oreshkin
Dmitri Carpov
Nicolas Chapados
Yoshua Bengio
AI4TS
131
1,067
0
24 May 2019
Deep Dynamical Modeling and Control of Unsteady Fluid Flows
Deep Dynamical Modeling and Control of Unsteady Fluid Flows
Jeremy Morton
F. Witherden
A. Jameson
Mykel J. Kochenderfer
AI4CE
74
165
0
18 May 2018
An Empirical Evaluation of Generic Convolutional and Recurrent Networks
  for Sequence Modeling
An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
Shaojie Bai
J. Zico Kolter
V. Koltun
DRL
101
4,851
0
04 Mar 2018
Deep learning for universal linear embeddings of nonlinear dynamics
Deep learning for universal linear embeddings of nonlinear dynamics
Bethany Lusch
J. Nathan Kutz
Steven L. Brunton
81
1,261
0
27 Dec 2017
Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition
Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition
Naoya Takeishi
Yoshinobu Kawahara
Takehisa Yairi
51
374
0
12 Oct 2017
Deeper, Broader and Artier Domain Generalization
Deeper, Broader and Artier Domain Generalization
Da Li
Yongxin Yang
Yi-Zhe Song
Timothy M. Hospedales
OOD
132
1,453
0
09 Oct 2017
Learning Deep Neural Network Representations for Koopman Operators of
  Nonlinear Dynamical Systems
Learning Deep Neural Network Representations for Koopman Operators of Nonlinear Dynamical Systems
Enoch Yeung
Soumya Kundu
Nathan Oken Hodas
AI4CE
85
387
0
22 Aug 2017
Attention Is All You Need
Attention Is All You Need
Ashish Vaswani
Noam M. Shazeer
Niki Parmar
Jakob Uszkoreit
Llion Jones
Aidan Gomez
Lukasz Kaiser
Illia Polosukhin
3DV
811
132,725
0
12 Jun 2017
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
David Salinas
Valentin Flunkert
Jan Gasthaus
AI4TSUQCVBDL
98
2,134
0
13 Apr 2017
Modeling Long- and Short-Term Temporal Patterns with Deep Neural
  Networks
Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks
Guokun Lai
Wei-Cheng Chang
Yiming Yang
Hanxiao Liu
BDLAI4TS
115
2,027
0
21 Mar 2017
Overcoming catastrophic forgetting in neural networks
Overcoming catastrophic forgetting in neural networks
J. Kirkpatrick
Razvan Pascanu
Neil C. Rabinowitz
J. Veness
Guillaume Desjardins
...
A. Grabska-Barwinska
Demis Hassabis
Claudia Clopath
D. Kumaran
R. Hadsell
CLL
374
7,587
0
02 Dec 2016
Instance Normalization: The Missing Ingredient for Fast Stylization
Instance Normalization: The Missing Ingredient for Fast Stylization
Dmitry Ulyanov
Andrea Vedaldi
Victor Lempitsky
OOD
180
3,714
0
27 Jul 2016
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
2.1K
150,433
0
22 Dec 2014
An Empirical Investigation of Catastrophic Forgetting in Gradient-Based
  Neural Networks
An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks
Ian Goodfellow
M. Berk Mirza
Xia Da
Aaron Courville
Yoshua Bengio
163
1,455
0
21 Dec 2013
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