| 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 | 360 | 2017 |
| Predictive coding: a theoretical and experimental review B Millidge, A Seth, CL Buckley arXiv preprint arXiv:2107.12979, 2021 | 155 | 2021 |
| Pretraining language models with human preferences T Korbak, K Shi, A Chen, RV Bhalerao, C Buckley, J Phang, SR Bowman, ... International Conference on Machine Learning, 17506-17533, 2023 | 126 | 2023 |
| Learning action-oriented models through active inference A Tschantz, AK Seth, CL Buckley PLoS computational biology 16 (4), e1007805, 2020 | 114 | 2020 |
| Predictive coding approximates backprop along arbitrary computation graphs B Millidge, A Tschantz, CL Buckley Neural Computation 34 (6), 1329-1368, 2022 | 113 | 2022 |
| 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 | 105 | 2022 |
| 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 | 101 | 2020 |
| 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 | 97 | 2021 |
| 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 | 87 | 2000 |
| 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 | 81 | 2016 |
| Whence the expected free energy? B Millidge, A Tschantz, CL Buckley Neural Computation 33 (2), 447-482, 2021 | 79 | 2021 |
| Reinforcement learning through active inference A Tschantz, B Millidge, AK Seth, CL Buckley arXiv preprint arXiv:2002.12636, 2020 | 77 | 2020 |
| Scaling active inference A Tschantz, M Baltieri, AK Seth, CL Buckley 2020 international joint conference on neural networks (ijcnn), 1-8, 2020 | 72 | 2020 |
| Neural complexity and structural connectivity L Barnett, CL Buckley, S Bullock Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 79 (5 …, 2009 | 71 | 2009 |
| PID control as a process of active inference with linear generative models M Baltieri, CL Buckley Entropy 21 (3), 257, 2019 | 67 | 2019 |
| Optimization in “self‐modeling” complex adaptive systems RA Watson, CL Buckley, R Mills Complexity 16 (5), 17-26, 2011 | 65 | 2011 |
| Simulating homeostatic, allostatic and goal-directed forms of interoceptive control using active inference A Tschantz, L Barca, D Maisto, CL Buckley, AK Seth, G Pezzulo Biological Psychology 169, 108266, 2022 | 62 | 2022 |
| 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 | 61 | 2011 |
| Associative memory in gene regulation networks R Watson, CL Buckley, R Mills, A Davies MIT Press, 2010 | 60 | 2010 |
| An active inference implementation of phototaxis M Baltieri, CL Buckley Artificial Life Conference Proceedings, 36-43, 2017 | 56 | 2017 |
