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2023
C. Chatzis, M. Pfeffer, P. Lind and E. A. Ataman. A Time-aware Tensor Decomposition for Tracking Evolving Patterns In MLSP'23: IEEE International Workshop on Machine Learning for Signal Processing. IEEE, 2023.
2022
D. T. Schroeder, J. Langguth, L. Burchard, K. Pogorelov and P. G. Lind. "The connectivity network underlying the German’s Twittersphere: a testbed for investigating information spreading phenomena." Scientific Reports 12, no. 1 (2022).PDF icon s41598-022-07961-3.pdf (1.61 MB)
2020
S. Pontes-Filho, P. Lind, A. Yazidi, J. Zhang, H. L. Hammer, G. B. M. Mello, I. Sandvig, G. Tufte and S. Nichele. EvoDynamic: A Framework for the Evolution of Generally Represented Dynamical Systems and Its Application to Criticality In International Conference on the Applications of Evolutionary Computation (Part of EvoStar). Cham: Springer, 2020.
D. T. Schroeder, P. Lind, K. Pogorelov and J. Langguth. A Framework for Interaction-based Propagation Analysis in Online Social Networks In Complex Networks. Springer, 2020.
D. T. Schroeder, P. Lind, K. Pogorelov and J. Langguth. A Framework for Interaction-based Propagation Analysis in Online Social Networks. Complex Networks, 2020.
S. Pontes-Filho, P. Lind, A. Yazidi, J. Zhang, H. L. Hammer, G. B. M. Mello, I. Sandvig, G. Tufte and S. Nichele. "A neuro-inspired general framework for the evolution of stochastic dynamical systems: Cellular automata, random Boolean networks and echo state networks towards criticality." Cognitive Neurodynamics 14 (2020): 1-18.