Publications of A Levina

Effenberger; Jost, J.; Levina, A.: Self-organization in Balanced State Networks by STDP and Homeostatic Plasticity. PLoS Computational Biology 11 (9), e1004420 (2015)

Effenberger, F.; Jost, J.; Levina, A.: Self-organization in balanced state networks by STDP and homeostatic plasticity. PLoS Computational Biology 11 (9), pp. 1 - 30 (2015)

Levina, A.; Herrmann, J.: The Abelian distribution. Stochastics and Dynamics 14 (3), 1450001 (2013)

Uhlig, M.; Levina, A.; Geisel, T.; Herrmann, J.: Critical dynamics in associative memory networks. Frontiers in Computational Neuroscience 7, 87 (2013)

Nagler, J.; Levina, A.; Timme, M.: Impact of single links in competitive percolation. Nature Physics 7 (3), pp. 265 - 270 (2011)

Levina, A.; Herrmann, J.; Geisel, T.: Phase transitions towards criticality in a neural system with adaptive interactions. Physical Review Letters 102 (11), 118110 (2009)

Levina, A.; Herrmann, M.; Geisel, T.: Dynamical synapses causing self-organized criticality in neural networks. Nature Physics 3 (12), pp. 857 - 860 (2007)

Levina, A.; Ernst, U.; Herrmann, M.: Criticality of avalanche dynamics in adaptive recurrent networks. Neurocomputing 70 (10-12), pp. 1877 - 1881 (2007)

Levina, A.; Herrmann, J.; Geisel, T.: Theoretical neuroscience of self‐organized criticality: from formal approaches to realistic models. In: Criticality in Neural Systems, 20, pp. 417 - 436 (Eds. Plenz, D.; Niebur, E.; Schuster, H.). Wiley-VCH, Weinheim, Germany (2014)

Hamidi, M.; Khajehabdollahi, S.; Giannakakis, E.; Schäfer, T.; Levina, A.; Wu, C.: Modular Growth of Hierarchical Networks: Efficient, General, and Robust Curriculum Learning. In: ALIFE 2024: Proceedings of the 2024 Artificial Life Conference. 2024 Conference on Artificial Life, Copenhagen, Denmark, July 22, 2024 - July 26, 2024. (2024)

Giannakakis, E.; Khajehabdollahi, S.; Levina, A.: Environmental variability and network structure determine the optimal plasticity mechanisms in embodied agents. In: ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference, pp. 157 - 166 (Eds. Iizuka, H.; Suzuki, K.; Uno, R.; Damiano, L.; Spychala, N. et al.). ALIFE 2023: Ghost in the Machine: The 2021 Conference on Artificial Life, Sapporo, Japan, July 24, 2023 - July 28, 2023. MIT Press (2023)

Khajehabdollahi, S.; Giannakakis, E.; Buendia, V.; Martius, G.; Levina, A.: Locally adaptive cellular automata for goal-oriented self-organization. In: ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference, pp. 410 - 419 (Eds. Iizuka, H.; Suzuki, K.; Uno, R.; Damiano, L.; Spychala, N. et al.). ALIFE 2023: Ghost in the Machine: The 2021 Conference on Artificial Life, Sapporo, Japan, July 24, 2023 - July 28, 2023. MIT Press (2023)

Khajehabdollahi, S.; Giannakakis, E.; Prosi, J.; Levina, A.: Reservoir computing with self-organizing neural oscillators. In: Artificial Life Conference Proceedings, Vol. 2021, 78. ALIFE 2021: The 2021 Conference on Artificial Life, Praha, Czech Republic, July 19, 2021 - July 23, 2021. MIT Press (2021)

Prosi, J.; Khajehabdollahi, S.; Giannakakis, E.; Martius, G.; Levina, A.: The dynamical regime and its importance for evolvability, task performance and generalization. In: Artificial Life Conference Proceedings, Vol. 2021, 79. ALIFE 2021: The 2021 Conference on Artificial Life, Praha, Czech Republic, July 19, 2021 - July 23, 2021. MIT Press (2021)

Khajehabdollahi, S.; Martius, G.; Levina, A.: Assessing Aesthetics of Generated Abstract Images Using Correlation Structure. In: 2019 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 306 - 313. IEEE Symposium Series on Computational Intelligence (SSCI 2019), Xiamen, China, December 06, 2019 - December 09, 2019. IEEE, Piscataway, NJ, USA (2019)

Levina, A.; Herrmann, M.; Geisel, T.: Dynamical synapses give rise to a power-law distribution of neuronal avalanches. In: Advances in Neural Information Processing Systems 18, Vol. 18, pp. 771 - 778 (Eds. Saul, L.; Schölkopf, B.; Platt, J.). Nineteenth Annual Conference on Neural Information Processing Systems (NIPS 2005), Vancouver, BC, Canada, December 05, 2005 - December 08, 2005. MIT Press, Cambridge, MA, USA (2006)

Giannakakis, E.; Vinogradov, O.; Buendía, V.; Khajehabdollahi, S.; Levina, A.: Local excitation and lateral inhibition enable the simultaneous processing of multiple signals in recurrent neural networks. In Journal of Computational Neuroscience, 52 (Supplement 1), O5, pp. S8 - S9. 32nd Annual Computational Neuroscience Meeting (CNS*2023), Leipzig, Germany, July 15, 2023 - July 19, 2023. Kluwer Academic Publishers, Boston (2024)

Zeraati, R.; Khajehabdollahi, S.; Giannakakis, E.; Schafer, T.; Martius, G.; Levina, A.: Long timescales needed for memory tasks arise from distinct mecha- nisms shaped by learning curricula. In Computational and Systems Neuroscience Meeting (COSYNE 2024), T-35, pp. 47 - 48. Computational and Systems Neuroscience Meeting (COSYNE 2024), Lisboa, Portugal, February 29, 2024 - March 05, 2024. (2024)

Zeraati, R.; Khajehabdollahi, S.; Giannakakis, E.; Schäfer, T.; Martius, G.; Levina, A.: Role of single-neuron and network-mediated timescales in recurrent neural networks solving long-memory tasks. In Bernstein Conference 2023, CT 4. Bernstein Conference 2023, Berlin, Germany, September 26, 2023 - September 29, 2023. (2023)

Levina, A.: Near-critical optimality: sensitivity and confidence trade offs. In Workshop on Optimality, evolutionary trade-offs, Pareto theory and degeneracy in neuronal modeling (CNS*2023). Workshop on Optimality, evolutionary trade-offs, Pareto theory and degeneracy in neuronal modeling (CNS*2023), Leipzig, Germany, July 18, 2023 - July 19, 2023. (2023)