Publications

Linares Barranco, A., Prono, L., Limbacher, T., Frenkel, C., Legenstein, R., & Indiveri, G. (2023). Implementación del acelerador neuromórfico de SNNs ReckON en MPSoC. JCER 2023.

Diaz-Romero, S., Canas Moreno, S., Piñero Fuentes, E., Paluch, M., & Linares Barranco, A. (2023). Una implementación de la Teoría de control de bucle cerrado basado en eventos dispersos (SECLOC). JCER 2023.

Farias, A., Piñero Fuentes, E., Rios Navarro, A., & Linares Barranco, A. (2023). Servitization of a Neuromorphic Robotic Arm: A Microservices Approach. JP 2023.

Rios Navarro, A., Piñero Fuentes, E., Canas Moreno, S., Javed, A., Harkin, J., & Linares Barranco, A. (2023). LIPSFUS: A neuromorphic dataset for audio-visual sensory fusion of lip Reading. ISCAS 2023.

Casanueva-Morato, D., Ayuso-Martinez, A., Dominguez-Morales, J. P., Jimenez-Fernandez, A., Jumenez-Moreno, G., & Perez-Peña, F. (2023). Bio-inspired spike-based Hippocampus and Posterior Parietal Cortex models for robot navigation and environment pseudo-mapping. Submitted to Wiley.

Urgese, G., Rios Navarro, A., Linares Barranco, A., Stewart C, T., & Michmizos, K. (2023). Editorial: Powering the next-generation IoT applications: new tools and emerging technologies for the development of Neuromorphic System of Systems. Frontiers in Neuroscience.

Canas Moreno, S., Piñero Fuentes, E., Rios Navarro, A., Cascado Caballero, D., Perez Peña, F., & Linares Barranco, A. (2023). Towards Neuromorphic FPGA-based Infrastructures for a Robotic Arm. Autonomous Robots.

Frenkel, C., Bol, D., & Indiveri, G. (2023). Bottom-Up and Top-Down Approaches for the Design of Neuromorphic Processing Systems: Tradeoffs and Synergies Between Natural and Artificial Intelligence. Proceedings of the IEEE.

Ortner, T., Pes, L., Gentinetta, J., Frenkel, C., & Pantazi, A. (2023). Online Spatio-Temporal Learning with Target Projection. IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS).

Petschenig, H., & Legenstein, R. (2023). Quantized Rewiring: Hardware-aware training of sparse deep neural networks. Neuromorphic Computing and Engineering.

Kraisnikovic, C., Stathopoulos, S., Prodromakis, T., & Legenstein, R. (2023). Fault Pruning: Robust Training of Neural Networks with Memristive Weights. 20th International Conference on Unconventional Computation and Natural Computation.

Piñero Fuentes, E., Canas Moreno, S., Rios Navarro, A., Cascado Caballero, D., Gomez-Rodriguez, F., Jimenez-Fernandez, A., & Linares Barranco, A. (2022). Multiprocesamiento empotrado para control robotico Neuromorfico mediante Redes Neuronales Pulsantes. JP 2022.

Linares-Barranco, A., Piñero-Fuentes, E., Canas-Moreno, S., Rios-Navarro, A., Maryada, C. W., Zhao, J., Zendrikov, D., & Indiveri, G. (2022). Towards hardware Implementation of WTA for CPG-based control of a Spiking Robotic Arm. 2022 International Symposium on Circuits and Systems (ISCAS), accepted.

Piñero-Fuentes, E., Canas-Moreno, S., Rios-Navarro, A., Cascado-Caballero, D., Jimenez-Fernandez, A., & Linares-Barranco, A. (2022). An MPSoC-based on-line Edge Infrastructure for Embedded Neuromorphic Robotic Controllers. 2022 International Symposium on Circuits and Systems (ISCAS), accepted.

Limbacher, T., Özdenizci, O., & Legenstein, R. (2022). Memory-enriched computation and learning in spiking neural networks through Hebbian plasticity. ArXiv Preprint ArXiv:2205.11276.

Bohnstingl, T., Šurina, A., Fabre, M., Demirag, Y., Frenkel, C., Payvand, M., Indiveri, G., & Pantazi, A. (2022). Biologically-inspired training of spiking recurrent neural networks with neuromorphic hardware. IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS).

Bohnstingl, T., Woźniak, S., Pantazi, A., & Eleftheriou, E. (2022). Online Spatio-Temporal Learning in Deep Neural Networks. IEEE Transactions on Neural Networks and Learning Systems.

Frenkel, C., & Indiveri, G. (2022). ReckOn: A 28nm Sub-mm² Task-Agnostic Spiking Recurrent Neural Network Processor Enabling On-Chip Learning over Second-Long Timescales. IEEE International Solid-State Circuits Conference (ISSCC).

Huang, J., Stathopoulos, S., Serb, A., & Prodromakis, T. (2022). NeuroPack: An Algorithm-level Python-based Simulator for Memristor-empowered Neuro-inspired Computing. Frontiers in Nanotechnology.

Kraisnikovic, C., Maass, W., & Legenstein, R. (2021). Spike-based symbolic computations on bit strings and numbers. Neuro-Symbolic Artificial Intelligence: The State of the Art, 214–234.

Traub, M., Legenstein, R., & Otte, S. (2021). Many-Joint Robot Arm Control with Recurrent Spiking Neural Networks. 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Demirag, Y., Frenkel, C., Payvand, M., & Indiveri, G. (2021). Online Training of Spiking Recurrent Neural Networks with Phase-Change Memory Synapses. ArXiv Preprint ArXiv:2108.01804v2.

Salaj, D., Subramoney, A., Kraisnikovic, C., Bellec, G., Legenstein, R., & Maass, W. (2021). Spike frequency adaptation supports network computations on temporally dispersed information. ELife.

Subramoney, A., Bellec, G., Scherr, F., Legenstein, R., & Maass, W. (2021). Revisiting the role of synaptic plasticity and network dynamics for fast learning in spiking neural networks. BioRxiv.

Demirag, Y., Moro, F., Dalgaty, T., Navarro, G., Frenkel, C., Indiveri, G., Vianello, E., & Payvand, M. (2021). PCM-trace: Scalable Synaptic Eligibility Traces with Resistivity Drift of Phase-Change Materials. 2021 28th IEEE International Conference on Electronics, Circuits and Systems (ICECS), accepted.

Limbacher, T., & Legenstein, R. (2020). H-Mem: Harnessing synaptic plasticity with Hebbian Memory Networks. Advances in Neural Information Processing Systems 33.

Bohnstingl, T., Pantazi, A., & Eleftheriou, E. (2020). Accelerating Spiking Neural Networks using Memristive Crossbar Arrays. 2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS), 1–4.

Bohnstingl, T., Woźniak, S., Maass, W., Pantazi, A., & Eleftheriou, E. (2020). Online spatio-temporal learning in deep neural networks. ArXiv Preprint ArXiv:2007.12723.

Linares-Barranco, A., Perez-Peña, F., Jimenez-Fernandez, A., & Chicca, E. (2020). ED-BioRob: A Neuromorphic Robotic Arm With FPGA-Based Infrastructure for Bio-Inspired Spiking Motor Controllers. Frontiers in Neurorobotics.

Giotis, C., Serb, A., Stathopoulos, S., Michalas, L., Khiat, A., & Prodromakis, T. (2020). Bidirectional Volatile Signatures of Metal–Oxide Memristors—Part I: Characterization. IEEE Transactions on Electron Devices.

Giotis, C., Serb, A., Stathopoulos, S., Michalas, L., & Prodromakis, T. (2020). Bidirectional Volatile Signatures of Metal–Oxide Memristors—Part II: Modeling. IEEE Transactions on Electron Devices.