Kris De Meyer
Kris De Meyer
Verified email at kcl.ac.uk - Homepage
TitleCited byYear
Stochastic diffusion optimisation: the application of partial evaluation and stochastic recruitment
K De Meyer, SJ Nasuto, MJ Bishop
Springer Verlag, 2006
63*2006
Time for Change? Climate Science Reconsidered: Report of the UCL Policy Commission on Communicating Climate Science, 2014
CG Rapley, K De Meyer, J Carney, R Clarke, C Howarth, N Smith, ...
UCL Policy Commission on Communicating Climate Science, University College …, 2014
37*2014
Unsupervised learning of overlapping image components using divisive input modulation
MW Spratling, K De Meyer, R Kompass
Computational intelligence and neuroscience 2009, 2009
352009
Foundations of stochastic diffusion search
K De Meyer
University of Reading, 2004
292004
Stochastic diffusion: Using recruitment for search
K De Meyer, JM Bishop, SJ Nasuto
Evolvability and interaction: evolutionary substrates of communication …, 2003
252003
Culture and climate change: Narratives
J Smith, R Tyszczuk, R Butler
Shed, 2014
202014
Explorations in stochastic diffusion search: Soft-and hardware implementations of biologically inspired spiking neuron stochastic diffusion networks
K De Meyer
Technical Report KDM/JMB/2000, 2000
202000
Communicating neurons: A connectionist spiking neuron implementation of stochastic diffusion search
SJ Nasuto, JM Bishop, K De Meyer
Neurocomputing 72 (4-6), 704-712, 2009
182009
Multiplicative gain modulation arises through unsupervised learning in a predictive coding model of cortical function
K De Meyer, MW Spratling
Neural computation 23 (6), 1536-1567, 2011
162011
Small-world effects in lattice stochastic diffusion search
K De Meyer, JM Bishop, SJ Nasuto
International Conference on Artificial Neural Networks, 147-152, 2002
162002
Climate science reconsidered
C Rapley, K De Meyer
Nature Climate Change 4 (9), 745, 2014
152014
Attention through self-synchronisation in the spiking neuron stochastic diffusion network
K De Meyer, JM Bishop, SJ Nasuto
Consc. and Cogn 9 (2), 81-81, 2000
142000
A model of non-linear interactions between cortical top-down and horizontal connections explains the attentional gating of collinear facilitation
K De Meyer, MW Spratling
Vision research 49 (5), 553-568, 2009
132009
A model of partial reference frame transforms through pooling of gain-modulated responses
K De Meyer, MW Spratling
Cerebral Cortex 23 (5), 1230-1239, 2012
102012
Dynamic knowledge representation in connectionist systems
JM Bishop, SJ Nasuto, K De Meyer
International Conference on Artificial Neural Networks, 308-313, 2002
82002
Multiple resolution mapping for efficient mobile robot navigation
K De Meyer, O Lemon, U Nehmzow
University of Manchester, 1997
71997
Implementation of the spiking neuron stochastic diffusion network on parallel hardware
T Morey, K De-Meyer, SJ Nasuto, JM Bishop
62000
Recruiting robots perform stochastic diffusion search
JM Bishop, K De Meyer, SJ Nasuto
Int Rob Auto J 5 (2), 143-144, 2018
12018
The Role of Feedback in the Determination of Figure and Ground: A Combined Behavioral & Modeling Study
LA Watling, MW Spratling, K De Meyer, MH Johnson
Proceedings of the Annual Meeting of the Cognitive Science Society 29 (29), 2007
12007
Interactive comment on “Telling the boiling frog what he needs to know: why climate change risks should be plotted as probability over time” by Simon Sharpe
K De Meyer
2019
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