Incremental sequence learning

By Arnaud Destrebecqz, Axel Cleeremans. 1996

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Ta-Chu Kao
2. Christian Henning
3. Benjamin Ehret
4. Johannes von Oswald
5. Maria R. Cervera
6. Kristopher T. Jensen
7. Gido M. van de Ven
8. Gyuhak Kim

Citations in the corpus

• Natural continual learning: success is a journey, not (just) a destination (2021, methodology): “We thus considered an augmented version of the stroke MNIST dataset [SMNIST; de Jong, 2016].”
• Continual Representation Learning for Biometric Identification (2020, neutral): “Continual learning is also named lifelong learning [46, 55, 57], incremental learning [7, 48, 54] and sequential learning [5, 10] in previous works.”
• Continual learning in recurrent neural networks (2020, methodology): “In the Stroke MNIST (SMNIST) dataset (de Jong, 2016), MNIST images (LeCun et al., 1998) are represented as sequences of pen displacements, that result in the original digits when drawn in order.”
• Continual Learning in Recurrent Neural Networks with Hypernetworks (2020, methodology): “The number of iterations was set according to the the number of digits in the sequences used in a given SMNIST experiment.”