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Christopher L. Buckley
Christopher L. Buckley
Verified email at sussex.ac.uk - Homepage
Title
Cited by
Cited by
Year
The free energy principle for action and perception: A mathematical review
CL Buckley, CS Kim, S McGregor, AK Seth
Journal of Mathematical Psychology 81, 55-79, 2017
3202017
Learning action-oriented models through active inference
A Tschantz, AK Seth, CL Buckley
PLoS computational biology 16 (4), e1007805, 2020
972020
Lattice Boltzmann BGK simulation of nonlinear sound waves: the development of a shock front
JM Buick, CL Buckley, CA Greated, J Gilbert
Journal of Physics A: Mathematical and General 33 (21), 3917, 2000
802000
Predictive coding approximates backprop along arbitrary computation graphs
B Millidge, A Tschantz, CL Buckley
Neural Computation 34 (6), 1329-1368, 2022
772022
Evolutionary connectionism: algorithmic principles underlying the evolution of biological organisation in evo-devo, evo-eco and evolutionary transitions
RA Watson, R Mills, CL Buckley, K Kouvaris, A Jackson, ST Powers, ...
Evolutionary biology 43, 553-581, 2016
692016
Neural complexity and structural connectivity
L Barnett, CL Buckley, S Bullock
Physical Review E 79 (5), 051914, 2009
682009
Optimization in “self‐modeling” complex adaptive systems
RA Watson, CL Buckley, R Mills
Complexity 16 (5), 17-26, 2011
602011
How particular is the physics of the free energy principle?
M Aguilera, B Millidge, A Tschantz, CL Buckley
Physics of Life Reviews 40, 24-50, 2022
592022
Scaling active inference
A Tschantz, M Baltieri, AK Seth, CL Buckley
2020 international joint conference on neural networks (ijcnn), 1-8, 2020
592020
Predictive coding: a theoretical and experimental review
B Millidge, A Seth, CL Buckley
arXiv preprint arXiv:2107.12979, 2021
572021
Whence the expected free energy?
B Millidge, A Tschantz, CL Buckley
Neural Computation 33 (2), 447-482, 2021
572021
Reinforcement learning through active inference
A Tschantz, B Millidge, AK Seth, CL Buckley
arXiv preprint arXiv:2002.12636, 2020
572020
PID control as a process of active inference with linear generative models
M Baltieri, CL Buckley
Entropy 21 (3), 257, 2019
542019
Global adaptation in networks of selfish components: Emergent associative memory at the system scale
RA Watson, R Mills, CL Buckley
Artificial Life 17 (3), 147-166, 2011
542011
An active inference implementation of phototaxis
M Baltieri, CL Buckley
arXiv preprint arXiv:1707.01806, 2017
522017
Associative memory in gene regulation networks
R Watson, CL Buckley, R Mills, A Davies
MIT Press, 2010
482010
On the relationship between active inference and control as inference
B Millidge, A Tschantz, AK Seth, CL Buckley
Active Inference: First International Workshop, IWAI 2020, Co-located with …, 2020
472020
Predictions in the eye of the beholder: an active inference account of Watt governors
M Baltieri, CL Buckley, J Bruineberg
arXiv preprint arXiv:2006.11495, 2020
302020
“If you can't be with the one you love, love the one you're with”: How individual habituation of agent interactions improves global utility
AP Davies, RA Watson, R Mills, CL Buckley, J Noble
Artificial Life 17 (3), 167-181, 2011
302011
Active inference in robotics and artificial agents: Survey and challenges
P Lanillos, C Meo, C Pezzato, AA Meera, M Baioumy, W Ohata, ...
arXiv preprint arXiv:2112.01871, 2021
292021
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