Slawek Smyl

Orcid: 0000-0003-2548-6695

According to our database1, Slawek Smyl authored at least 14 papers between 2010 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Contextually enhanced ES-dRNN with dynamic attention for short-term load forecasting.
Neural Networks, January, 2024

2023
Local and Global Trend Bayesian Exponential Smoothing Models.
CoRR, 2023

Forecasting Cryptocurrency Prices Using Contextual ES-adRNN with Exogenous Variables.
Proceedings of the Computational Science - ICCS 2023, 2023

2022
A Hybrid Residual Dilated LSTM and Exponential Smoothing Model for Midterm Electric Load Forecasting.
IEEE Trans. Neural Networks Learn. Syst., 2022

Recurrent Neural Networks for Forecasting Time Series with Multiple Seasonality: A Comparative Study.
CoRR, 2022

ES-dRNN with Dynamic Attention for Short-Term Load Forecasting.
Proceedings of the International Joint Conference on Neural Networks, 2022

2021
Ensembles of localised models for time series forecasting.
Knowl. Based Syst., 2021

ES-dRNN: A Hybrid Exponential Smoothing and Dilated Recurrent Neural Network Model for Short-Term Load Forecasting.
CoRR, 2021

2020
Forecasting across time series databases using recurrent neural networks on groups of similar series: A clustering approach.
Expert Syst. Appl., 2020

A Hybrid Residual Dilated LSTM end Exponential Smoothing Model for Mid-Term Electric Load Forecasting.
CoRR, 2020

3ETS+RD-LSTM: A New Hybrid Model for Electrical Energy Consumption Forecasting.
Proceedings of the Neural Information Processing - 27th International Conference, 2020

2017
Forecasting Across Time Series Databases using Long Short-Term Memory Networks on Groups of Similar Series.
CoRR, 2017

2011
Fuzzy prophet: parameter exploration in uncertain enterprise scenarios.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2011

2010
DataGarage: Warehousing Massive Performance Data on Commodity Servers.
Proc. VLDB Endow., 2010


  Loading...