Dmitrii Zendrikov

According to our database, Dmitrii Zendrikov authored at least 10 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Neuromorphic dreaming as a pathway to efficient learning in artificial agents.

Ingo Blakowski, Dmitrii Zendrikov, Giacomo Indiveri, Cristiano Capone

Neuromorph. Comput. Eng., 2025

Genetic Motifs as a Blueprint for Mismatch-Tolerant Neuromorphic Computing.

Tommaso Boccato, Dmitrii Zendrikov, Nicola Toschi, Giacomo Indiveri

Proceedings of the IEEE International Symposium on Circuits and Systems, 2025

2024

The vitals for steady nucleation maps of spontaneous spiking coherence in autonomous two-dimensional neuronal networks.

Dmitrii Zendrikov, Alexander Paraskevov

Neural Networks, 2024

Spike-based computational primitives to reproduce neural dynamics in the parietal cortex during motor preparation.

Leonardo Parrilla, Matteo Filippini, Dmitrii Zendrikov, Patrizia Fattori, Giacomo Indiveri

Neuromorph. Comput. Eng., 2024

Neuromorphic dreaming: A pathway to efficient learning in artificial agents.

Ingo Blakowski, Dmitrii Zendrikov, Cristiano Capone, Giacomo Indiveri

CoRR, 2024

Waves and Symbols in Neuromorphic Hardware: From Analog Signal Processing to Digital Computing on the Same Computational Substrate.

Dmitrii Zendrikov, Alessio Franci, Giacomo Indiveri

Proceedings of the 58th Asilomar Conference on Signals, 2024

2023

Brain-inspired methods for achieving robust computation in heterogeneous mixed-signal neuromorphic processing systems.

Dmitrii Zendrikov, Sergio M. G. Solinas, Giacomo Indiveri

Neuromorph. Comput. Eng., September, 2023

2022

Towards hardware Implementation of WTA for CPG-based control of a Spiking Robotic Arm.

Alejandro Linares-Barranco, Enrique Piñero-Fuentes, Salvador Canas-Moreno, Antonio Rios-Navarro, Maryada, Chenxi Wu, Jingyue Zhao, Dmitrii Zendrikov, Giacomo Indiveri

Proceedings of the IEEE International Symposium on Circuits and Systems, 2022

2021

Emergent population activity in metric-free and metric networks of neurons with stochastic spontaneous spikes and dynamic synapses.

Dmitrii Zendrikov, Alexander Paraskevov

Neurocomputing, 2021

Supervised training of spiking neural networks for robust deployment on mixed-signal neuromorphic processors.

Julian Büchel, Dmitrii Zendrikov, Sergio M. G. Solinas, Giacomo Indiveri, Dylan R. Muir

CoRR, 2021