23 citations · 35 across the 7 of their papers we have counts for
7 papers
Probing neural representations of scene perception in a hippocampally dependent task using artificial neural networks
Markus Frey, Christian F. Doeller, Caswell Barry
Deep artificial neural networks (DNNs) trained through backpropagation provide effective models of the mammalian visual system, accurately capturing the hierarchy of neural respons…
Functional Connectome: Approximating Brain Networks with Artificial Neural Networks
Sihao Liu, Augustine N Mavor-Parker, Caswell Barry
We aimed to explore the capability of deep learning to approximate the function instantiated by biological neural circuits-the functional connectome. Using deep neural networks, we…
Temporally Extended Successor Representations
Matthew J. Sargent, Peter J. Bentley, Caswell Barry +1
We present a temporally extended variation of the successor representation, which we term t-SR. t-SR captures the expected state transition dynamics of temporally extended actions…
Using Forwards-Backwards Models to Approximate MDP Homomorphisms
Augustine N. Mavor-Parker, Matthew J. Sargent, Christian Pehle +3
Reinforcement learning agents must painstakingly learn through trial and error what sets of state-action pairs are value equivalent -- requiring an often prohibitively large amount…
How to Stay Curious while Avoiding Noisy TVs using Aleatoric Uncertainty Estimation
Augustine N. Mavor-Parker, Kimberly A. Young, Caswell Barry +1
Exploration in environments with sparse rewards is difficult for artificial agents. Curiosity driven learning -- using feed-forward prediction errors as intrinsic rewards -- has ac…
MEMO: A Deep Network for Flexible Combination of Episodic Memories
Andrea Banino, Adrià Puigdomènech Badia, Raphael Köster +7
Recent research developing neural network architectures with external memory have often used the benchmark bAbI question and answering dataset which provides a challenging number o…
Generalisation of structural knowledge in the hippocampal-entorhinal system
James C. R. Whittington, Timothy H. Muller, Shirley Mark +2
A central problem to understanding intelligence is the concept of generalisation. This allows previously learnt structure to be exploited to solve tasks in novel situations differi…