Transductive LSTM for time-series prediction: An application to weather forecasting

2020/05/01 by Zahra Karevan, Johan A.K. Suykens · 10 citations

paper · doi:10.1016/j.neunet.2019.12.030

Cited by

• ATLO-ML: Adaptive Time-Length Optimizer for Machine Learning -- Insights from Air Quality Forecasting
• IndexNet: Timestamp and Variable-Aware Modeling for Time Series Forecasting
• ProtoTS: Learning Hierarchical Prototypes for Explainable Time Series Forecasting
• Adaptive von Mises-Fisher Likelihood Loss for Supervised Deep Time Series Hashing
• S²Transformer: Scalable Structured Transformers for Global Station Weather Forecasting
• One-Embedding-Fits-All: Efficient Zero-Shot Time Series Forecasting by a Model Zoo
• Text Reinforcement for Multimodal Time Series Forecasting
• Global weather forecasting through deep learning: applications and challenges
• The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting
• Time-series forecasting for nonlinear high-dimensional system using hybrid method combining autoencoder and multi-parallelized quantum long short-term memory and gated recurrent unit