Publications

Nilsson, M., Pina, T. J., Khacef, L., Liwicki, F., Chicca, E., & Sandin, F. (2023). A Comparison of Temporal Encoders for Neuromorphic Keyword Spotting with Few Neurons. In International Joint Conference on Neural Networks (IJCNN): Proceedings (Proceedings of the International Joint Conference on Neural Networks). IEEE. https://doi.org/10.1109/IJCNN54540.2023.10191938

Richter, O., Greatorex, H., Hučko, B., Cotteret, M., Soares Girão, W., Janotte, E., Mastella, M., & Chicca, E. (2023). A Subthreshold Second-Order Integration Circuit for Versatile Synaptic Alpha Kernel and Trace Generation. In AMC ICONS2023 (pp. 1-4). Article 33 ACM Press. https://doi.org/10.1145/3589737.3606008

Wang, X., Risi, N., Talavera Martínez, E., Chicca, E., & Azzopardi, G. (2023). Fall detection with event-based data: A case study. In N. Tsapatsoulis (Ed.), Computer Analysis of Images and Patterns: 20th International Conference, CAIP 2023 Limassol, Cyprus, September 25–28, 2023 Proceedings, Part II (pp. 33-42). (Lecture Notes in Computer Science; Vol. 14185). Springer. https://doi.org/10.1007/978-3-031-44240-7_4

Schoepe, T., & Chicca, E. (2023). Finding the Goal: Insect-Inspired Spiking Neural Network for Heading Error Estimation. In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023 (pp. 4727-4733). (IEEE International Conference on Intelligent Robots and Systems). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IROS55552.2023.10342210

Kugele, A., Pfeil, T., Pfeiffer, M., & Chicca, E. (2023). How Many Events Make an Object? Improving Single-frame Object Detection on the 1 Mpx Dataset. In Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023 (pp. 3913-3922). (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2023-June). IEEE Computer Society. https://doi.org/10.1109/CVPRW59228.2023.00406

Cotteret, M., Richter, O., Mastella, M., Greatorex, H., Janotte, E., Soares Girão, W., Ziegler, M., & Chicca, E. (2023). Robust Spiking Attractor Networks with a Hard Winner-Take-All Neuron Circuit. In 2023 IEEE International Symposium on Circuits and Systems (ISCAS): Proceedings IEEE. https://doi.org/10.1109/ISCAS46773.2023.10181513

Mastella, M., Greatorex, H., Cotteret, M., Janotte, E., Soares Girão, W., Richter, O., & Chicca, E. (2023). Synaptic Normalisation for On-Chip Learning in Analog CMOS Spiking Neural Networks. In ACM ICONS2023: Proceedings of the 2023 International Conference on Neuromorphic Systems (pp. 1-4). Article 34 ACM Press. https://doi.org/10.1145/3589737.3606007

Kugele, A., Pfeil, T., Pfeiffer, M., & Chicca, E. (2022). Hybrid SNN-ANN: Energy-Efficient Classification and Object Detection for Event-Based Vision. In C. Bauckhage, J. Gall, & A. Schwing (Eds.), Pattern Recognition (pp. 297–312). (Pattern Recognition. DAGM GCPR), (Lecture Notes in Computer Science; Vol. 13024). Springer. https://doi.org/10.1007/978-3-030-92659-5_19

Mastella, M., & Chicca, E. (2021). A Hardware-friendly Neuromorphic Spiking Neural Network for Frequency Detection and Fine Texture Decoding. In 2021 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 1-5). Article 9401377 IEEE. https://doi.org/10.1109/ISCAS51556.2021.9401377

Dabbous, A., Mastella, M., Natarajan, A., Chicca, E., Valle, M., & Bartolozzi, C. (2021). Artificial Bio-inspired Tactile Receptive Fields for Edge Orientation Classification. In 2021 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 1-5). Article 9401749 IEEE. https://doi.org/10.1109/ISCAS51556.2021.9401749

Covi, E., Duong, Q. T., Lancaster, S., Havel, V., Coignus, J., Barbot, J., Richter, O., Klein, P., Chicca, E., Grenouillet, L., Dimoulas, A., Mikolajick, T., & Slesazeck, S. (2021). Ferroelectric Tunneling Junctions for Edge Computing. In 2021 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 1-5). Article 9401800 IEEE. https://doi.org/10.1109/ISCAS51556.2021.9401800

Pedretti, G., Milo, V., Hashemkhani, S., Mannocci, P., Melnic, O., Chicca, E., & Ielmini, D. (2020). A Spiking Recurrent Neural Network with Phase Change Memory Synapses for Decision Making. In 2020 IEEE International Symposium on Circuits and Systems (ISCAS) IEEE. https://doi.org/10.1109/ISCAS45731.2020.9180513

Schoepe, T., Gutierrez-Galan, D., Dominguez-Morales, J. P., Jimenez-Fernandez, A., Linares-Barranco, A., & Chicca, E. (2020). Live Demonstration: Neuromorphic Sensory Integration for Combining Sound Source Localization and Collision Avoidance. In 2020 IEEE International Symposium on Circuits and Systems (ISCAS) IEEE. https://doi.org/10.1109/ISCAS45731.2020.9181257

Schoepe, T., Gutierrez-Galan, D., Dominguez-Morales, J. P., Jimenez-Fernandez, A., Linares-Barranco, A., & Chicca, E. (2019). Neuromorphic Sensory Integration for Combining Sound Source Localization and Collision Avoidance. In 2019 IEEE Biomedical Circuits and Systems Conference (BioCAS) IEEE. https://doi.org/10.1109/BIOCAS.2019.8919202

Suresh, B., Bertele, M., Breyer, E. T., Klein, P., Mulaosmanovic, H., Mikolajick, T., Slesazeck, S., & Chicca, E. (2019). Simulation of integrate-and-fire neuron circuits using HfO₂-based ferroelectric field effect transistors. In 2019 26th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2019 (pp. 229-232). Article 8965004 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICECS46596.2019.8965004

Milo, V., Chicca, E., & Ielmini, D. (2018). Brain-Inspired Recurrent Neural Network with Plastic RRAM Synapses. In 2018 IEEE International Symposium on Circuits and Systems (ISCAS) IEEE. https://doi.org/10.1109/ISCAS.2018.8351523

Donati, E., Perez-Peña, F., Bartolozzi, C., Indiveri, G., & Chicca, E. (2018). Open-Loop Neuromorphic Controller Implemented on VLSI Devices. In 2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob) IEEE. https://doi.org/10.1109/BIOROB.2018.8487937

Milo, V., Pedretti, G., Laudato, M., Bricalli, A., Ambrosi, E., Bianchi, S., Chicca, E., & Ielmini, D. (2018). Resistive switching synapses for unsupervised learning in feed-forward and recurrent neural networks. In 2018 IEEE International Symposium on Circuits and Systems (ISCAS) IEEE. https://doi.org/10.1109/ISCAS.2018.8351824

Milo, V., Ielmini, D., & Chicca, E. (2017). Attractor networks and associative memories with STDP learning in RRAM synapses. In 2017 IEEE International Electron Devices Meeting (IEDM) IEEE. https://doi.org/10.1109/IEDM.2017.8268369

Perez-Peña, F., Leñero-Bardallo, J. A., Linares-Barranco, A., & Chicca, E. (2017). Towards Bioinspired Close-Loop Local Motor Control: A Simulated Approach Supporting Neuromorphic Implementations. In 2017 IEEE International Symposium on Circuits and Systems (ISCAS) IEEE. https://doi.org/10.1109/ISCAS.2017.8050808

Huayaney, F. L. M., & Chicca, E. (2016). A VLSI Implementation of a calcium-based plasticity learning model. In 2016 IEEE International Symposium on Circuits and Systems (ISCAS) IEEE. https://doi.org/10.1109/ISCAS.2016.7527248

Chang, J., Sonkusale, S., Yalcin, M., Ogunfunmi, T., Vanderwalle, J., Zhu, W.-P., Liu, Z., Chang, R. C.-H., Chicca, E., Callegari, S., Chu, C.-C., Dudek, P., Lee, G. G., & Chowdhury, M. (2016). Current And Emergent Topics. In F. Maloberti, & A. C. Davies (Eds.), A Short History of Circuits And Systems (pp. 255-265). River Publishers.

Biolek, D., Carrara, S., Chicca, E., Corinto, F., Georgiou, J., Linares-Barranco, B., Prodromakis, T., Spiga, S., & Tetzlaff, R. (2016). EU COST action IC1401 - Pushing the frontiers of memristive devices to systems. In 2016 18th Mediterranean Electrotechnical Conference (MELECON) IEEE. https://doi.org/10.1109/MELCON.2016.7495309

Nease, S., & Chicca, E. (2016). Floating-Gate-Based Intrinsic Plasticity with Low-Voltage Rate Control. In 2016 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 2507-2510). IEEE. https://doi.org/10.1109/ISCAS.2016.7539102

Schirmer, M., Stradolini, F., Carrara, S., & Chicca, E. (2016). FPGA-based Approach for Automatic Peak Detection in Cyclic Voltammetry. In 2016 IEEE International Conference on Electronics, Circuits and Systems (ICECS) (pp. 65-68). IEEE. https://doi.org/10.1109/ICECS.2016.7841133

Staar, B., Schirmer, M., Bai-Rossi, C., Micheli, G. D., Carrara, S., & Chicca, E. (2015). A neural approach to drugs monitoring for personalized medicine. In 2015 International Joint Conference on Neural Networks (IJCNN) IEEE. https://doi.org/10.1109/IJCNN.2015.7280611

Milde, M. B., Bertrand, O. J. N., Benosman, R., Egelhaaf, M., & Chicca, E. (2015). Bioinspired event-driven collision avoidance algorithm based on optic flow. In 2015 International Conference on Event-based Control, Communication, and Signal Processing (EBCCSP) IEEE. https://doi.org/10.1109/EBCCSP.2015.7300673

Nease, S., & Chicca, E. (2015). Power-Efficient Estimation of Silicon Neuron Firing Rates with Floating-Gate Transistors. In 2015 European Conference on Circuit Theory and Design (ECCTD) IEEE. https://doi.org/10.1109/ECCTD.2015.7300005

Perez-Peña, F., Linares-Barranco, A., & Chicca, E. (2014). An approach to motor control for spike-based neuromorphic robotics. In 2014 IEEE Biomedical Circuits and Systems Conference (BioCAS) Proceedings (pp. 528-531). IEEE. https://doi.org/10.1109/BioCAS.2014.6981779

Ramachandran, H., Weber, S., Aamir, S. A., & Chicca, E. (2014). Neuromorphic Circuits for Short-term Plasticity with Recovery Control. In 2014 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 858-861). IEEE. https://doi.org/10.1109/ISCAS.2014.6865271

Chicca, E., Schmuker, M., & Nawrot, M. P. (2014). Neuromorphic Sensors, Olfaction. In D. Jaeger, & R. Jung (Eds.), Encyclopedia of Computational Neuroscience Springer New York LLC. https://doi.org/10.1007/978-1-4614-7320-6_119-2

Rost, T., Ramachandran, H., Nawrot, M. P., & Chicca, E. (2013). A neuromorphic approach to auditory pattern recognition in cricket phonotaxis. In 2013 European Conference on Circuit Theory and Design (ECCTD) IEEE. https://doi.org/10.1109/ECCTD.2013.6662247

Sheik, S., Chicca, E., & Indiveri, G. (2012). Exploiting Device Mismatch in Neuromorphic VLSI Systems to Implement Axonal Delays. In The 2012 International Joint Conference on Neural Networks (IJCNN) (pp. 1940-1945). IEEE. https://doi.org/10.1109/IJCNN.2012.6252636

Corneil, D., Sonnleithner, D., Neftci, E., Chicca, E., Cook, M., Indiveri, G., & Douglas, R. J. (2012). Function approximation with uncertainty propagation in a VLSI spiking neural network. In The 2012 International Joint Conference on Neural Networks (IJCNN) (pp. 2990-2996). IEEE. https://doi.org/10.1109/IJCNN.2012.6252780

Corneil, D., Sonnleithner, D., Neftci, E., Chicca, E., Cook, M., Indiveri, G., & Douglas, R. J. (2012). Real-time inference in a VLSI spiking neural network. In 2012 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 2425-2428). IEEE. https://doi.org/10.1109/ISCAS.2012.6271788

Neftci, E., Binas, J., Chicca, E., Indiveri, G., & Douglas, R. J. (2012). Systematic Construction of Finite State Automata Using VLSI Spiking Neurons. In T. J. Prescott, N. F. Lepora, A. Mura, & P. F. M. J. Verschure (Eds.), Biomimetic and Biohybrid Systems: First International Conference, Living Machines 2012, Barcelona, Spain, July 9-12, 2012. Proceedings (Vol. 7375, pp. 382-383). (Lecture Notes in Computer Science; Vol. 7375). Springer Berlin / Heidelberg. https://doi.org/10.1007/978-3-642-31525-1_52

Indiveri, G., & Chicca, E. (2011). A VLSI neuromorphic device for implementing spike-based neural networks. In B. Apolloni, S. Bassis, A. Esposito, & C. F. Morabito (Eds.), Neural Nets WIRN11 - Proceedings of the 21st Italian Workshop on Neural Nets (Vol. 234, pp. 305-316). ( Frontiers in Artificial Intelligence and Applications; Vol. 234). IOS Press. https://doi.org/10.3233/978-1-60750-972-1-305

Sheik, S., Stefanini, F., Neftci, E., Chicca, E., & Indiveri, G. (2011). Systematic configuration and automatic tuning of neuromorphic systems. In 2011 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 873-876). IEEE. https://doi.org/10.1109/ISCAS.2011.5937705

Beyeler, M., Stefanini, F., Proske, H., Galizia, G., & Chicca, E. (2010). Exploring Olfactory Sensory Networks: Simulations and Hardware Emulation. In 2010 Biomedical Circuits and Systems Conference (BioCAS) (pp. 270-273). IEEE. https://doi.org/10.1109/BIOCAS.2010.5709623

Neftci, E., Chicca, E., Cook, M., Indiveri, G., & Douglas, R. (2010). Live demonstration: State-dependent sensory processing in networks of VLSI spiking neurons. In ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems (pp. 2788). Article 5537006 IEEE. https://doi.org/10.1109/ISCAS.2010.5537006

Indiveri, G., Stefanini, F., & Chicca, E. (2010). Spike-based learning with a generalized integrate and fire silicon neuron. In Proceedings of 2010 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 1951-1954). IEEE. https://doi.org/10.1109/ISCAS.2010.5536980

Neftci, E., Chicca, E., Cook, M., Indiveri, G., & Douglas, R. J. (2010). State-dependent sensory processing in networks of VLSI spiking neurons. In Proceedings of 2010 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 2789-2792). IEEE. https://doi.org/10.1109/ISCAS.2010.5537007

Neftci, E., Chicca, E., Indiveri, G., Slotine, J.-J., & Douglas, R. J. (2008). Contraction Properties of VLSI Cooperative Competitive Neural Networks of Spiking Neurons. In J. C. Platt, D. Koller, Y. Singer, & S. Roweis (Eds.), Advances in Neural Information Processing Systems (NIPS) (Vol. 20, pp. 1073-1080). The MIT Press.

Tapson, J., Diaz, J., Sander, D., Gurari, N., Chicca, E., Pouliquen, P., & Etienne-Cummings, R. (2008). The Feeling of Color: A Haptic Feedback Device for the Visually Disabled. In 2008 IEEE Biomedical Circuits and Systems Conference (BIOCAS) (pp. 381-384). IEEE. https://doi.org/10.1109/BIOCAS.2008.4696954

Chicca, E., Indiveri, G., & Douglas, R. J. (2007). Context dependent amplification of both rate and event-correlation in a VLSI network of spiking neurons. In B. Schölkopf, J. Platt, & T. Hofmann (Eds.), Advances in Neural Information Processing Systems 19 - Proceedings of the 2006 Conference (pp. 257-264). (Advances in Neural Information Processing Systems). MIT Press.

Wang, H.-P., Chicca, E., Indiveri, G., & Sejnowski, T. J. (2007). Reliable Computation in Noisy Backgrounds Using Real-Time Neuromorphic Hardware. In 2007 IEEE Biomedical Circuits and Systems Conference (BioCAS) (pp. 71-74). IEEE. https://doi.org/10.1109/BIOCAS.2007.4463311

Chicca, E., Lichtsteiner, P., Delbruck, T., Indiveri, G., & Douglas, R. J. (2006). Modeling Orientation Selectivity Using a Neuromorphic Multi-Chip System. In 2006 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 1235-1238). IEEE. https://doi.org/10.1109/ISCAS.2006.1692815

Chicca, E., Indiveri, G., & Douglas, R. J. (2004). An event-based VLSI network of integrate-and-fire neurons. In 2004 IEEE International Symposium on Circuits and Systems (ISCAS) (Vol. 5). IEEE. https://doi.org/10.1109/ISCAS.2004.1329536

Indiveri, G., Chicca, E., & Douglas, R. J. (2004). A VLSI reconfigurable network of integrate-and-fire neurons with spike-based learning synapses. In Proceedings of 12th European Symposium on Artificial Neural Networks (ESANN04) (pp. 405-410). ESANN.

Rubin, D. B., Chicca, E., & Indiveri, G. (2004). Characterizing the firing properties of an adaptive analog VLSI neuron. In AJ. Ijspeert, M. Murata, & N. Wakamiya (Eds.), Biologically Inspired Approaches to Advanced Information Technology (pp. 189-200). (Lecture Notes in Computer Science; Vol. 3141). Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/978-3-540-27835-1_15

Rubin, D. B.-D., Chicca, E., & Indiveri, G. (2004). Firing proprieties of an adaptive analog VLSI neuron. In Proceedings of Bio-ADIT 2004 , Lausanne (pp. 314-327)

Chicca, E., Indiveri, G., & Douglas, R. J. (2003). An adaptive silicon synapse. In Proceedings of the 2003 International Symposium on Circuits and Systems ISCAS '03 (pp. I81-I84). IEEE. https://doi.org/10.1109/ISCAS.2003.1205505

Chicca, E., & Fusi, S. (2001). Stochastic synaptic plasticity in deterministic aVLSI networks of spiking neurons. In F. Rattay (Ed.), Proceedings of the World Congress on Neuroinformatics (pp. 468-477). (ARGESIM Reports). ARGESIM/ASIM Verlag.