Conor Heins

798 total citations
21 papers, 327 citations indexed

About

Conor Heins is a scholar working on Cognitive Neuroscience, Statistical and Nonlinear Physics and Artificial Intelligence. According to data from OpenAlex, Conor Heins has authored 21 papers receiving a total of 327 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cognitive Neuroscience, 7 papers in Statistical and Nonlinear Physics and 4 papers in Artificial Intelligence. Recurrent topics in Conor Heins's work include Neural dynamics and brain function (9 papers), Advanced Thermodynamics and Statistical Mechanics (5 papers) and Embodied and Extended Cognition (5 papers). Conor Heins is often cited by papers focused on Neural dynamics and brain function (9 papers), Advanced Thermodynamics and Statistical Mechanics (5 papers) and Embodied and Extended Cognition (5 papers). Conor Heins collaborates with scholars based in Germany, United Kingdom and United States. Conor Heins's co-authors include Karl Friston, Lancelot Da Costa, Thomas Parr, Iain D. Couzin, Maxwell J. D. Ramstead, Grigorios A. Pavliotis, Kai Ueltzhöffer, Beren Millidge, Noor Sajid and Brennan Klein and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Trends in Ecology & Evolution and Physics Reports.

In The Last Decade

Conor Heins

19 papers receiving 321 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Conor Heins Germany	10	188	51	41	38	35	21	327
Erik Hoel United States	10	247 1.3×	74 1.5×	20 0.5×	11 0.3×	53 1.5×	15	526
Juan‐Carlos Letelier Chile	12	123 0.7×	12 0.2×	37 0.9×	33 0.9×	12 0.3×	20	470
Chetan Prakash United States	10	253 1.3×	12 0.2×	44 1.1×	51 1.3×	40 1.1×	13	433
Lancelot Da Costa United Kingdom	13	317 1.7×	103 2.0×	65 1.6×	52 1.4×	61 1.7×	27	491
Hans Liljenström Sweden	15	357 1.9×	78 1.5×	9 0.2×	25 0.7×	110 3.1×	58	704
Christopher L. Buckley United Kingdom	17	537 2.9×	72 1.4×	74 1.8×	92 2.4×	150 4.3×	55	903
Gennaro Auletta Italy	13	112 0.6×	86 1.7×	51 1.2×	21 0.6×	107 3.1×	46	479
Fernando Soler Toscano Spain	11	109 0.6×	38 0.7×	12 0.3×	21 0.6×	159 4.5×	35	441
Jorge Navarro Spain	14	63 0.3×	19 0.4×	9 0.2×	40 1.1×	38 1.1×	54	514
Ensor Rafael Palacios United Kingdom	4	237 1.3×	17 0.3×	40 1.0×	56 1.5×	26 0.7×	5	325

Countries citing papers authored by Conor Heins

Since Specialization

Citations

This map shows the geographic impact of Conor Heins's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Conor Heins with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Conor Heins more than expected).

Fields of papers citing papers by Conor Heins

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Conor Heins. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Conor Heins. The network helps show where Conor Heins may publish in the future.

Co-authorship network of co-authors of Conor Heins

This figure shows the co-authorship network connecting the top 25 collaborators of Conor Heins. A scholar is included among the top collaborators of Conor Heins based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Conor Heins. Conor Heins is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Wei, Ran, et al.. (2025). Navigation Under Uncertainty: Trajectory Prediction and Occlusion Reasoning with Switching Dynamical Systems. 1–6.

Friston, Karl, Thomas Parr, Conor Heins, et al.. (2025). Gradient-Free De Novo Learning. Entropy. 27(9). 992–992.

Heins, Conor, et al.. (2025). As One and Many: Relating Individual and Emergent Group-Level Generative Models in Active Inference. Entropy. 27(2). 143–143. 2 indexed citations

Heins, Conor, et al.. (2025). Introducing ActiveInference.jl: A Julia Library for Simulation and Parameter Estimation with Active Inference Models. Entropy. 27(1). 62–62. 1 indexed citations

Friston, Karl, Conor Heins, Tim Verbelen, et al.. (2025). From pixels to planning: scale-free active inference. PubMed. 5. 1521963–1521963. 4 indexed citations

Friston, Karl, Lancelot Da Costa, Alexander Tschantz, et al.. (2024). Supervised structure learning. Biological Psychology. 193. 108891–108891. 12 indexed citations

Friston, Karl, Alex Kiefer, Alexander Tschantz, et al.. (2024). Designing ecosystems of intelligence from first principles. TU/e Research Portal. 3(1). 12 indexed citations

Heins, Conor, Beren Millidge, Lancelot Da Costa, et al.. (2024). Collective behavior from surprise minimization. Proceedings of the National Academy of Sciences. 121(17). e2320239121–e2320239121. 20 indexed citations

Friston, Karl, Lancelot Da Costa, Conor Heins, et al.. (2023). Path integrals, particular kinds, and strange things. Physics of Life Reviews. 47. 35–62. 44 indexed citations

10.

Friston, Karl, Thomas Parr, Conor Heins, et al.. (2023). Federated inference and belief sharing. Neuroscience & Biobehavioral Reviews. 156. 105500–105500. 13 indexed citations

11.

Ramstead, Maxwell J. D., Conor Heins, Beren Millidge, et al.. (2023). On Bayesian mechanics: a physics of and by beliefs. Interface Focus. 13(3). 20220029–20220029. 53 indexed citations

12.

Friston, Karl, Lancelot Da Costa, Noor Sajid, et al.. (2023). The free energy principle made simpler but not too simple. Physics Reports. 1024. 1–29. 51 indexed citations

13.

Heins, Conor, Beren Millidge, Brennan Klein, et al.. (2022). pymdp: A Python library for active inference indiscrete state spaces. The Journal of Open Source Software. 7(73). 4098–4098. 1 indexed citations

14.

Heins, Conor & Lancelot Da Costa. (2022). Sparse coupling and Markov blankets. Physics of Life Reviews. 42. 33–39. 3 indexed citations

15.

Couzin, Iain D. & Conor Heins. (2022). Emerging technologies for behavioral research in changing environments. Trends in Ecology & Evolution. 38(4). 346–354. 40 indexed citations

16.

Heins, Conor. (2022). Particular flows and attracting sets. Physics of Life Reviews. 42. 43–48. 1 indexed citations

17.

Ramstead, Maxwell J. D., et al.. (2022). Epistemic Communities under Active Inference. Entropy. 24(4). 476–476. 24 indexed citations

18.

Parr, Thomas, Lancelot Da Costa, Conor Heins, Maxwell J. D. Ramstead, & Karl Friston. (2021). Memory and Markov Blankets. Entropy. 23(9). 1105–1105. 4 indexed citations

19.

Tomlinson, Samuel B., et al.. (2018). What do you know? ERP evidence for immediate use of common ground during online reference resolution. Cognition. 182. 275–285. 7 indexed citations

20.

Both, Martin, Lee Ann Campbell, Brandon K. Harvey, et al.. (2017). Sparse convolutional coding for neuronal assembly detection. MPG.PuRe (Max Planck Society). 30. 3675–3685. 4 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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