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Found 8 papers, 5 papers with code
PreDiff: Precipitation Nowcasting with Latent Diffusion Models
We conduct empirical studies on two datasets: N-body MNIST, a synthetic dataset with chaotic behavior, and SEVIR, a real-world precipitation nowcasting dataset.
Cross-Frequency Time Series Meta-Forecasting
Meta-forecasting is a newly emerging field which combines meta-learning and time series forecasting.
First De-Trend then Attend: Rethinking Attention for Time-Series Forecasting
Transformer-based models have gained large popularity and demonstrated promising results in long-term time-series forecasting in recent years.
Domain Adaptation for Time Series Forecasting via Attention Sharing
Recently, deep neural networks have gained increasing popularity in the field of time series forecasting.
Inter-Series Attention Model for COVID-19 Forecasting
COVID-19 pandemic has an unprecedented impact all over the world since early 2020.
HULK: An Energy Efficiency Benchmark Platform for Responsible Natural Language Processing
We introduce HULK, a multi-task energy efficiency benchmarking platform for responsible natural language processing.
You May Not Need Order in Time Series Forecasting
Time series forecasting with limited data is a challenging yet critical task.
Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting
Time series forecasting is an important problem across many domains, including predictions of solar plant energy output, electricity consumption, and traffic jam situation.
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