SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting

17 June 2025

Papers citing "SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting"

8 / 8 papers shown

Title
DAM: Towards A Foundation Model for Time Series Forecasting L. N. Darlow Qiwen Deng Ahmed Hassan Martin Asenov Rajkarn Singh Artjom Joosen Adam Barker Amos Storkey AI4TS AI4CE 69 4 0 25 Jul 2024
A decoder-only foundation model for time-series forecasting Abhimanyu Das Weihao Kong Rajat Sen Yichen Zhou AI4TS AI4CE 113 240 0 14 Oct 2023
iTransformer: Inverted Transformers Are Effective for Time Series Forecasting Yong Liu Tengge Hu Haoran Zhang Haixu Wu Shiyu Wang Lintao Ma Mingsheng Long AI4TS 93 547 0 10 Oct 2023
Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors Yong Liu Chenyu Li Jianmin Wang Mingsheng Long AI4TS 79 118 0 30 May 2023
Resurrecting Recurrent Neural Networks for Long Sequences Antonio Orvieto Samuel L. Smith Albert Gu Anushan Fernando Çağlar Gülçehre Razvan Pascanu Soham De 326 295 0 11 Mar 2023
FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting Tian Zhou Ziqing Ma Xue Wang Qingsong Wen Liang Sun Tao Yao Wotao Yin Rong Jin AI4TS 174 187 0 18 May 2022
Learning Deep Neural Network Representations for Koopman Operators of Nonlinear Dynamical Systems Enoch Yeung Soumya Kundu Nathan Oken Hodas AI4CE 74 387 0 22 Aug 2017
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks David Salinas Valentin Flunkert Jan Gasthaus AI4TS UQCV BDL 81 2,123 0 13 Apr 2017