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Filters: 1 is biblio_type:Poster and Author is Pedro Lind  [Reset Search]
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.
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.