research
∙
10/15/2022
Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution
Neuroscience has long been an important driver of progress in artificial...
share
research
∙
06/20/2022
When Does Re-initialization Work?
Re-initializing a neural network during training has been observed to im...
research
∙
05/18/2022
Maslow's Hammer for Catastrophic Forgetting: Node Re-Use vs Node Activation
Continual learning - learning new tasks in sequence while maintaining pe...
research
∙
05/31/2021
A study on the plasticity of neural networks
One aim shared by multiple settings, such as continual learning or trans...
research
∙
05/12/2021
CCN GAC Workshop: Issues with learning in biological recurrent neural networks
This perspective piece came about through the Generative Adversarial Col...
research
∙
05/11/2021
Spectral Normalisation for Deep Reinforcement Learning: an Optimisation Perspective
Most of the recent deep reinforcement learning advances take an RL-centr...
research
∙
04/16/2020
Continual Reinforcement Learning with Multi-Timescale Replay
In this paper, we propose a multi-timescale replay (MTR) buffer for impr...
research
∙
07/20/2019
Learning spatiotemporal signals using a recurrent spiking network that discretizes time
Learning to produce spatiotemporal sequences is a common task the brain ...
research
∙
02/01/2019
Policy Consolidation for Continual Reinforcement Learning
We propose a method for tackling catastrophic forgetting in deep reinfor...
research
∙
02/27/2018
A High GOPs/Slice Time Series Classifier for Portable and Embedded Biomedical Applications
Modern wearable rehabilitation devices and health support systems operat...
research
∙
02/20/2018
Continual Reinforcement Learning with Complex Synapses
Unlike humans, who are capable of continual learning over their lifetime...
research
∙
12/02/2016
