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Found 4 papers, 0 papers with code
PDMLP: Patch-based Decomposed MLP for Long-Term Time Series Forecastin
We attribute the effectiveness of these models largely to the adopted Patch mechanism, which enhances sequence locality to an extent yet fails to fully address the loss of temporal information inherent to the permutation-invariant self-attention mechanism.
Infomaxformer: Maximum Entropy Transformer for Long Time-Series Forecasting Problem
The Transformer architecture yields state-of-the-art results in many tasks such as natural language processing (NLP) and computer vision (CV), since the ability to efficiently capture the precise long-range dependency coupling between input sequences.
MTSMAE: Masked Autoencoders for Multivariate Time-Series Forecasting
Large-scale self-supervised pre-training Transformer architecture have significantly boosted the performance for various tasks in natural language processing (NLP) and computer vision (CV).
Multivariate Time Series Forecasting
Self-Supervised Learning
+1
Features Fusion Framework for Multimodal Irregular Time-series Events
Firstly, the complex features are extracted according to the irregular patterns of different events.
