Multi-resolution Time-Series Transformer for Long-term Forecasting
Fuente:
arXiv
Saved in:
| Main Authors: | Zhang, Yitian, Ma, Liheng, Pal, Soumyasundar, Zhang, Yingxue, Coates, Mark |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
CKGConv: General Graph Convolution with Continuous Kernels
by: Ma, Liheng, et al.
Published: (2024)
by: Ma, Liheng, et al.
Published: (2024)
Plain Transformers Can be Powerful Graph Learners
by: Ma, Liheng, et al.
Published: (2025)
by: Ma, Liheng, et al.
Published: (2025)
GraphPPD: Posterior Predictive Modelling for Graph-Level Inference
by: Pal, Soumyasundar, et al.
Published: (2025)
by: Pal, Soumyasundar, et al.
Published: (2025)
FEval-TTC: Fair Evaluation Protocol for Test-Time Compute
by: Rumiantsev, Pavel, et al.
Published: (2025)
by: Rumiantsev, Pavel, et al.
Published: (2025)
SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting
by: Zhang, Yitian, et al.
Published: (2025)
by: Zhang, Yitian, et al.
Published: (2025)
C3PO: Optimized Large Language Model Cascades with Probabilistic Cost Constraints for Reasoning
by: Valkanas, Antonios, et al.
Published: (2025)
by: Valkanas, Antonios, et al.
Published: (2025)
Enhancing Logical Reasoning in Large Language Models through Graph-based Synthetic Data
by: Zhou, Jiaming, et al.
Published: (2024)
by: Zhou, Jiaming, et al.
Published: (2024)
Refining Answer Distributions for Improved Large Language Model Reasoning
by: Pal, Soumyasundar, et al.
Published: (2024)
by: Pal, Soumyasundar, et al.
Published: (2024)
Sparse Decomposition of Graph Neural Networks
by: Hu, Yaochen, et al.
Published: (2024)
by: Hu, Yaochen, et al.
Published: (2024)
SageFormer: Series-Aware Framework for Long-term Multivariate Time Series Forecasting
by: Zhang, Zhenwei, et al.
Published: (2023)
by: Zhang, Zhenwei, et al.
Published: (2023)
A Balanced Neuro-Symbolic Approach for Commonsense Abductive Logic
by: Cotnareanu, Joseph, et al.
Published: (2026)
by: Cotnareanu, Joseph, et al.
Published: (2026)
ATFNet: Adaptive Time-Frequency Ensembled Network for Long-term Time Series Forecasting
by: Ye, Hengyu, et al.
Published: (2024)
by: Ye, Hengyu, et al.
Published: (2024)
TimelyGPT: Extrapolatable Transformer Pre-training for Long-term Time-Series Forecasting in Healthcare
by: Song, Ziyang, et al.
Published: (2023)
by: Song, Ziyang, et al.
Published: (2023)
Leveraging 2D Information for Long-term Time Series Forecasting with Vanilla Transformers
by: Cheng, Xin, et al.
Published: (2024)
by: Cheng, Xin, et al.
Published: (2024)
MSHyper: Multi-Scale Hypergraph Transformer for Long-Range Time Series Forecasting
by: Shang, Zongjiang, et al.
Published: (2024)
by: Shang, Zongjiang, et al.
Published: (2024)
TimePro: Efficient Multivariate Long-term Time Series Forecasting with Variable- and Time-Aware Hyper-state
by: Ma, Xiaowen, et al.
Published: (2025)
by: Ma, Xiaowen, et al.
Published: (2025)
To See Far, Look Close: Evolutionary Forecasting for Long-term Time Series
by: Ma, Jiaming, et al.
Published: (2026)
by: Ma, Jiaming, et al.
Published: (2026)
iTransformer: Inverted Transformers Are Effective for Time Series Forecasting
by: Liu, Yong, et al.
Published: (2023)
by: Liu, Yong, et al.
Published: (2023)
TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting
by: Liu, Peiyuan, et al.
Published: (2024)
by: Liu, Peiyuan, et al.
Published: (2024)
SEMixer: Semantics Enhanced MLP-Mixer for Multiscale Mixing and Long-term Time Series Forecasting
by: Zhang, Xu, et al.
Published: (2026)
by: Zhang, Xu, et al.
Published: (2026)
Multivariate Long-term Time Series Forecasting with Fourier Neural Filter
by: Xu, Chenheng, et al.
Published: (2025)
by: Xu, Chenheng, et al.
Published: (2025)
Omni-Thinker: Scaling Multi-Task RL in LLMs with Hybrid Reward and Task Scheduling
by: Li, Derek, et al.
Published: (2025)
by: Li, Derek, et al.
Published: (2025)
PENGUIN: Enhancing Transformer with Periodic-Nested Group Attention for Long-term Time Series Forecasting
by: Sun, Tian, et al.
Published: (2025)
by: Sun, Tian, et al.
Published: (2025)
TimeExpert: Boosting Long Time Series Forecasting with Temporal Mix of Experts
by: Ma, Xiaowen, et al.
Published: (2025)
by: Ma, Xiaowen, et al.
Published: (2025)
Mixture-of-Linear-Experts for Long-term Time Series Forecasting
by: Ni, Ronghao, et al.
Published: (2023)
by: Ni, Ronghao, et al.
Published: (2023)
Multi-scale Transformer Pyramid Networks for Multivariate Time Series Forecasting
by: Zhang, Yifan, et al.
Published: (2023)
by: Zhang, Yifan, et al.
Published: (2023)
Dualformer: Time-Frequency Dual Domain Learning for Long-term Time Series Forecasting
by: Bai, Jingjing, et al.
Published: (2026)
by: Bai, Jingjing, et al.
Published: (2026)
TimeMachine: A Time Series is Worth 4 Mambas for Long-term Forecasting
by: Ahamed, Md Atik, et al.
Published: (2024)
by: Ahamed, Md Atik, et al.
Published: (2024)
WFTNet: Exploiting Global and Local Periodicity in Long-term Time Series Forecasting
by: Liu, Peiyuan, et al.
Published: (2023)
by: Liu, Peiyuan, et al.
Published: (2023)
Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting
by: Deng, Jinliang, et al.
Published: (2024)
by: Deng, Jinliang, et al.
Published: (2024)
Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting
by: Chen, Peng, et al.
Published: (2024)
by: Chen, Peng, et al.
Published: (2024)
InnerThoughts: Disentangling Representations and Predictions in Large Language Models
by: Chételat, Didier, et al.
Published: (2025)
by: Chételat, Didier, et al.
Published: (2025)
HardCore Generation: Generating Hard UNSAT Problems for Data Augmentation
by: Cotnareanu, Joseph, et al.
Published: (2024)
by: Cotnareanu, Joseph, et al.
Published: (2024)
Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping
by: Li, Zhe, et al.
Published: (2023)
by: Li, Zhe, et al.
Published: (2023)
xLSTMTime : Long-term Time Series Forecasting With xLSTM
by: Alharthi, Musleh, et al.
Published: (2024)
by: Alharthi, Musleh, et al.
Published: (2024)
Reasoning on a Budget: A Survey of Adaptive and Controllable Test-Time Compute in LLMs
by: Alomrani, Mohammad Ali, et al.
Published: (2025)
by: Alomrani, Mohammad Ali, et al.
Published: (2025)
DyG2Vec: Efficient Representation Learning for Dynamic Graphs
by: Alomrani, Mohammad Ali, et al.
Published: (2022)
by: Alomrani, Mohammad Ali, et al.
Published: (2022)
Timer-XL: Long-Context Transformers for Unified Time Series Forecasting
by: Liu, Yong, et al.
Published: (2024)
by: Liu, Yong, et al.
Published: (2024)
DRFormer: Multi-Scale Transformer Utilizing Diverse Receptive Fields for Long Time-Series Forecasting
by: Ding, Ruixin, et al.
Published: (2024)
by: Ding, Ruixin, et al.
Published: (2024)
AdaMixT: Adaptive Weighted Mixture of Multi-Scale Expert Transformers for Time Series Forecasting
by: Zhang, Huanyao, et al.
Published: (2025)
by: Zhang, Huanyao, et al.
Published: (2025)
Similar Items
-
CKGConv: General Graph Convolution with Continuous Kernels
by: Ma, Liheng, et al.
Published: (2024) -
Plain Transformers Can be Powerful Graph Learners
by: Ma, Liheng, et al.
Published: (2025) -
GraphPPD: Posterior Predictive Modelling for Graph-Level Inference
by: Pal, Soumyasundar, et al.
Published: (2025) -
FEval-TTC: Fair Evaluation Protocol for Test-Time Compute
by: Rumiantsev, Pavel, et al.
Published: (2025) -
SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting
by: Zhang, Yitian, et al.
Published: (2025)