3 papers
cs.LG2019
GRIm-RePR: Prioritising Generating Important Features for Pseudo-Rehearsal
Craig Atkinson, Brendan McCane, Lech Szymanski +1
Pseudo-rehearsal allows neural networks to learn a sequence of tasks without forgetting how to perform in earlier tasks. Preventing forgetting is achieved by introducing a generati…
cs.LG2018
Pseudo-Rehearsal: Achieving Deep Reinforcement Learning without Catastrophic Forgetting
Craig Atkinson, Brendan McCane, Lech Szymanski +1
Neural networks can achieve excellent results in a wide variety of applications. However, when they attempt to sequentially learn, they tend to learn the new task while catastrophi…
cs.LG2018
Pseudo-Recursal: Solving the Catastrophic Forgetting Problem in Deep Neural Networks
Craig Atkinson, Brendan McCane, Lech Szymanski +1
In general, neural networks are not currently capable of learning tasks in a sequential fashion. When a novel, unrelated task is learnt by a neural network, it substantially forget…