no code implementations • 26 Mar 2020 • Bernardo Pérez Orozco, Stephen J. Roberts
Recurrent neural networks (RNNs) are state-of-the-art in several sequential learning tasks, but they often require considerable amounts of data to generalise well.
1 code implementation • 26 Mar 2018 • Bernardo Pérez Orozco, Gabriele Abbati, Stephen Roberts
In this work, we directly tackle this task with a novel, fully end-to-end deep learning method for time series forecasting.
no code implementations • 15 May 2017 • Ivan Kiskin, Bernardo Pérez Orozco, Theo Windebank, Davide Zilli, Marianne Sinka, Kathy Willis, Stephen Roberts
The huge advances enjoyed by many application domains in recent years have been fuelled by the use of deep learning architectures trained on large data sets.