David Salinas
Mila - Quebec Artificial Intelligence Institute(CA)
Publications by Year
Research Areas
Time Series Analysis and Forecasting, Forecasting Techniques and Applications, Stock Market Forecasting Methods, Machine Learning and Data Classification, Advanced Multi-Objective Optimization Algorithms
Most-Cited Works
- → Deep Learning for Time Series Forecasting: Tutorial and Literature Survey(2022)280 cited
- → DeepAR: Probabilistic forecasting with autoregressive recurrent networks(2019)238 cited
- → Criteria for classifying forecasting methods(2019)197 cited
- On Challenges in Machine Learning Model Management(2015)
- → Probabilistic demand forecasting at scale(2017)122 cited
- GluonTS: Probabilistic and Neural Time Series Modeling in Python(2020)
- → Elastic Machine Learning Algorithms in Amazon SageMaker(2020)101 cited
- DataWig: Missing Value Imputation for Tables(2019)
- Probabilistic Forecasting with Spline Quantile Function RNNs(2019)