| Statistical mechanics of monod–wyman–changeux (mwc) models S Marzen, HG Garcia, R Phillips Journal of molecular biology 425 (9), 1433-1460, 2013 | 121 | 2013 |
| On the role of theory and modeling in neuroscience D Levenstein, VA Alvarez, A Amarasingham, H Azab, ZS Chen, ... Journal of Neuroscience 43 (7), 1074-1088, 2023 | 84 | 2023 |
| The evolution of lossy compression SE Marzen, S DeDeo Journal of The Royal Society Interface 14 (130), 20170166, 2017 | 59 | 2017 |
| Informational and causal architecture of discrete-time renewal processes SE Marzen, JP Crutchfield Entropy 17 (7), 4891-4917, 2015 | 46 | 2015 |
| Mathematically Modeling Prey-Catching Behavior of the Tomato Frog C Tyler, S Marzen, J Monroy Spora: A Journal of Biomathematics 8 (1), 1-6, 2022 | 42 | 2022 |
| Time resolution dependence of information measures for spiking neurons: Scaling and universality SE Marzen, MR DeWeese, JP Crutchfield Frontiers in computational neuroscience 9, 105, 2015 | 41 | 2015 |
| Predictive rate-distortion for infinite-order Markov processes SE Marzen, JP Crutchfield Journal of Statistical Physics 163, 1312-1338, 2016 | 39 | 2016 |
| Difference between memory and prediction in linear recurrent networks S Marzen Physical Review E 96 (3), 032308, 2017 | 38 | 2017 |
| Structure and Randomness of Continuous-Time, Discrete-Event Processes S Marzen, JP Crutchfield Journal of Statistical Physics 169 (2), 303-315, 2017 | 36 | 2017 |
| Nearly maximally predictive features and their dimensions SE Marzen, JP Crutchfield Physical Review E 95 (5), 051301, 2017 | 36 | 2017 |
| Informational and causal architecture of continuous-time renewal processes S Marzen, JP Crutchfield Journal of Statistical Physics 168, 109-127, 2017 | 31 | 2017 |
| Information anatomy of stochastic equilibria S Marzen, JP Crutchfield Entropy 16 (9), 4713-4748, 2014 | 29 | 2014 |
| Statistical Signatures of Structural Organization: The case of long memory in renewal processes SE Marzen, JP Crutchfield Physics Letters A 380 (17), 1517 - 1525, 2016 | 25 | 2016 |
| First-principles prediction of the information processing capacity of a simple genetic circuit M Razo-Mejia, S Marzen, G Chure, R Taubman, M Morrison, R Phillips Physical Review E 102 (2), 022404, 2020 | 22 | 2020 |
| Signatures of infinity: Nonergodicity and resource scaling in prediction, complexity, and learning JP Crutchfield, S Marzen Physical Review E 91 (5), 050106, 2015 | 22 | 2015 |
| Machine learning outperforms thermodynamics in measuring how well a many-body system learns a drive W Zhong, JM Gold, S Marzen, JL England, N Yunger Halpern Scientific Reports 11 (1), 9333, 2021 | 20 | 2021 |
| Optimized bacteria are environmental prediction engines SE Marzen, JP Crutchfield Physical Review E 98 (1), 012408, 2018 | 20 | 2018 |
| Memory and information processing in recurrent neural networks A Goudarzi, S Marzen, P Banda, G Feldman, C Teuscher, D Stefanovic arXiv preprint arXiv:1604.06929, 2016 | 19 | 2016 |
| Weak universality in sensory tradeoffs S Marzen, S DeDeo Physical Review E 94 (6), 060101, 2016 | 12 | 2016 |
| Maximum entropy models provide functional connectivity estimates in neural networks M Lamberti, M Hess, I Dias, M van Putten, J le Feber, S Marzen Scientific reports 12 (1), 9656, 2022 | 8 | 2022 |
Michael R DeWeeseProfessor of Physics and Neuroscience, University of California at BerkeleyAdresă de e-mail confirmată pe berkeley.edu
