Approximately Equivariant Recurrent Generative Models for Quasi-Periodic Time Series with a Progressive Training Scheme
Fuente:
arXiv
Saved in:
| Main Authors: | Fulek, Ruwen, Lange-Hegermann, Markus |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series
by: Soni, Juhi, et al.
Published: (2025)
by: Soni, Juhi, et al.
Published: (2025)
Investigation of the Impact of Synthetic Training Data in the Industrial Application of Terminal Strip Object Detection
by: Baumgart, Nico, et al.
Published: (2024)
by: Baumgart, Nico, et al.
Published: (2024)
On the Laplace Approximation as Model Selection Criterion for Gaussian Processes
by: Besginow, Andreas, et al.
Published: (2024)
by: Besginow, Andreas, et al.
Published: (2024)
Future Aware Safe Active Learning of Time Varying Systems using Gaussian Processes
by: Lange-Hegermann, Markus, et al.
Published: (2024)
by: Lange-Hegermann, Markus, et al.
Published: (2024)
Physics-informed Gaussian Processes as Linear Model Predictive Controller
by: Tebbe, Jörn, et al.
Published: (2024)
by: Tebbe, Jörn, et al.
Published: (2024)
Gaussian Process Regression for Inverse Problems in Linear PDEs
by: Li, Xin, et al.
Published: (2025)
by: Li, Xin, et al.
Published: (2025)
Generative Modeling of Approximately Periodic Time Series by a Posterior-Weighted Gaussian Process
by: Reich, Elias, et al.
Published: (2026)
by: Reich, Elias, et al.
Published: (2026)
Visual Car Brand Classification by Implementing a Synthetic Image Dataset Creation Pipeline
by: Lippemeier, Jan, et al.
Published: (2024)
by: Lippemeier, Jan, et al.
Published: (2024)
Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning
by: Tebbe, Jörn, et al.
Published: (2024)
by: Tebbe, Jörn, et al.
Published: (2024)
Robust Group Anomaly Detection for Quasi-Periodic Network Time Series
by: Yang, Kai, et al.
Published: (2025)
by: Yang, Kai, et al.
Published: (2025)
Quasi-Equivariant Metanetworks
by: Tran, Viet-Hoang, et al.
Published: (2026)
by: Tran, Viet-Hoang, et al.
Published: (2026)
Evaluating Time Series Foundation Models on Noisy Periodic Time Series
by: Gupta, Syamantak Datta
Published: (2025)
by: Gupta, Syamantak Datta
Published: (2025)
Approximation-Generalization Trade-offs under (Approximate) Group Equivariance
by: Petrache, Mircea, et al.
Published: (2023)
by: Petrache, Mircea, et al.
Published: (2023)
Symbol-Equivariant Recurrent Reasoning Models
by: Freinschlag, Richard, et al.
Published: (2026)
by: Freinschlag, Richard, et al.
Published: (2026)
Accelerating Quasi-Static Time Series Simulations with Foundation Models
by: Puech, Alban, et al.
Published: (2024)
by: Puech, Alban, et al.
Published: (2024)
PHAT: Modeling Period Heterogeneity for Multivariate Time Series Forecasting
by: Ma, Jiaming, et al.
Published: (2026)
by: Ma, Jiaming, et al.
Published: (2026)
Approximately Equivariant Neural Processes
by: Ashman, Matthew, et al.
Published: (2024)
by: Ashman, Matthew, et al.
Published: (2024)
Approximate Equivariance in Reinforcement Learning
by: Park, Jung Yeon, et al.
Published: (2024)
by: Park, Jung Yeon, et al.
Published: (2024)
Recurrent Interpolants for Probabilistic Time Series Prediction
by: Chen, Yu, et al.
Published: (2024)
by: Chen, Yu, et al.
Published: (2024)
Still Competitive: Revisiting Recurrent Models for Irregular Time Series Prediction
by: Joshi, Ankitkumar, et al.
Published: (2025)
by: Joshi, Ankitkumar, et al.
Published: (2025)
Gaussian Process Priors for Boundary Value Problems of Linear Partial Differential Equations
by: Huang, Jianlei, et al.
Published: (2024)
by: Huang, Jianlei, et al.
Published: (2024)
Recurrent Neural Goodness-of-Fit Test for Time Series
by: Zhang, Aoran, et al.
Published: (2024)
by: Zhang, Aoran, et al.
Published: (2024)
Accelerating the Generation of Molecular Conformations with Progressive Distillation of Equivariant Latent Diffusion Models
by: Lacombe, Romain, et al.
Published: (2024)
by: Lacombe, Romain, et al.
Published: (2024)
CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patterns
by: Lin, Shengsheng, et al.
Published: (2024)
by: Lin, Shengsheng, et al.
Published: (2024)
Wavelet Networks: Scale-Translation Equivariant Learning From Raw Time-Series
by: Romero, David W., et al.
Published: (2020)
by: Romero, David W., et al.
Published: (2020)
PRformer: Pyramidal Recurrent Transformer for Multivariate Time Series Forecasting
by: Yu, Yongbo, et al.
Published: (2024)
by: Yu, Yongbo, et al.
Published: (2024)
Deep Autocorrelation Modeling for Time-Series Forecasting: Progress and Prospects
by: Wang, Hao, et al.
Published: (2026)
by: Wang, Hao, et al.
Published: (2026)
Approximate Equivariance via Projection-based Regularisation
by: Berndt, Torben, et al.
Published: (2026)
by: Berndt, Torben, et al.
Published: (2026)
VarDrop: Enhancing Training Efficiency by Reducing Variate Redundancy in Periodic Time Series Forecasting
by: Kang, Junhyeok, et al.
Published: (2025)
by: Kang, Junhyeok, et al.
Published: (2025)
Improving Equivariant Model Training via Constraint Relaxation
by: Pertigkiozoglou, Stefanos, et al.
Published: (2024)
by: Pertigkiozoglou, Stefanos, et al.
Published: (2024)
Asynchronous Training Schemes in Distributed Learning with Time Delay
by: Wang, Haoxiang, et al.
Published: (2022)
by: Wang, Haoxiang, et al.
Published: (2022)
Flow Equivariant Recurrent Neural Networks
by: Keller, T. Anderson
Published: (2025)
by: Keller, T. Anderson
Published: (2025)
Interpretable Time Series Autoregression for Periodicity Quantification
by: Chen, Xinyu, et al.
Published: (2025)
by: Chen, Xinyu, et al.
Published: (2025)
Semi-Periodic Activation for Time Series Classification
by: Júnior, José Gilberto Barbosa de Medeiros, et al.
Published: (2024)
by: Júnior, José Gilberto Barbosa de Medeiros, et al.
Published: (2024)
Periodic Graph-Enhanced Multivariate Time Series Anomaly Detector
by: Li, Jia, et al.
Published: (2025)
by: Li, Jia, et al.
Published: (2025)
Times2D: Multi-Period Decomposition and Derivative Mapping for General Time Series Forecasting
by: Nematirad, Reza, et al.
Published: (2025)
by: Nematirad, Reza, et al.
Published: (2025)
Algebraic Priors for Approximately Equivariant Networks
by: Ali, Riccardo, et al.
Published: (2025)
by: Ali, Riccardo, et al.
Published: (2025)
BRATI: Bidirectional Recurrent Attention for Time-Series Imputation
by: Collado-Villaverde, Armando, et al.
Published: (2025)
by: Collado-Villaverde, Armando, et al.
Published: (2025)
Wavelet Probabilistic Recurrent Convolutional Network for Multivariate Time Series Classification
by: Yang, Pu, et al.
Published: (2025)
by: Yang, Pu, et al.
Published: (2025)
Deep State Space Recurrent Neural Networks for Time Series Forecasting
by: Inzirillo, Hugo
Published: (2024)
by: Inzirillo, Hugo
Published: (2024)
Similar Items
-
Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series
by: Soni, Juhi, et al.
Published: (2025) -
Investigation of the Impact of Synthetic Training Data in the Industrial Application of Terminal Strip Object Detection
by: Baumgart, Nico, et al.
Published: (2024) -
On the Laplace Approximation as Model Selection Criterion for Gaussian Processes
by: Besginow, Andreas, et al.
Published: (2024) -
Future Aware Safe Active Learning of Time Varying Systems using Gaussian Processes
by: Lange-Hegermann, Markus, et al.
Published: (2024) -
Physics-informed Gaussian Processes as Linear Model Predictive Controller
by: Tebbe, Jörn, et al.
Published: (2024)