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Institut für Mathematik

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Study Project: Computing with Spikes (Part I)

8.3073

Dozenten

Beschreibung

Spiking neural networks (SNNs) are models of brain computation in which individual neurons communicate with spikes, just like the brain does. Compared to more successful artificial neural network models (think Deep Nets), SNNs still raise a number of unique and challenging research questions: (i) How do you learn in a neural network when error-backpropagation doesn’t work? (ii) And can you do this with local update (plasticity) rules that use local information only? (iii) How do you learn a neural network or neuron model that uses spikes very efficiently and still finds a good representation of a continuous input stream?. The potential upsides of spiking nets: We can build specialized, neuromorphic hardware for spike-based networks that promises low-latency real-time, low-power and adaptive computation for the next generation of A.I.
In this context, the study project will follow the neuromorphic tradition of building a system that starts with spike-based sensing: An event-based stereo-vision setup with 2 artificial retinas and a stereo audio sensor for which we will implement an artificial cochlea ourselves. Our goal is to put state-of-the-art theories and algorithms for SNN computation to rigorous testing. We will thus challenge ourselves to tackle multi-modal multi-sensor real-time integration of information – an incredibly challenging technical task that our brain is purpose-built for and handles with ease. Step-by-step, we will tackle aspects of this problem in spiking neural network models that range from simple to complex, from “this-works-but-is-not-how-the-brain-does-it” to “this-is-closer-to-the-brain-but-really-hard-to-make-work”.
The project and accompanying interdisciplinary course are primarily aimed at Master students with an interest in one or more of the following themes: modeling networks of dynamical systems (plastic neurons), simulating spiking neural networks, low-level programming and engineering of A.I. systems using unconventional technologies, staying up to date and documenting state-of-the-art research in SNNs, or supporting a potentially quite complex project organisationally.

Weitere Angaben

Ort: 93/E12
Zeiten: Mo. 14:00 - 16:00 (wöchentlich), Do. 10:00 - 12:00 (wöchentlich)
Erster Termin: Donnerstag, 04.04.2024 10:00 - 12:00, Ort: 93/E12
Veranstaltungsart: Studienprojekt (Offizielle Lehrveranstaltungen)

Studienbereiche

  • Cognitive Science > Master-Programm

Past and Forthcoming Events

Publications

  • Asymptotics of a time-bounded cylinder model, with N. Aschenbruck and S. Bussmann, Probability in the Engineering and Informational Sciences, https://doi.org/10.1017/S0269964822000420
  • The method of cumulants for the normal approximation, with S. Jansen and K. Schubert, Probability Surveys 2022, Vol. 19, 185-270, https://doi.org/10.1214/22-PS7
  • Sedentary Random Waypoint, with C. Betken, arXiv:2009.02941
  • The Impact of Bit Errors on Intra-Session Network Coding with Heterogeneous Packet Lengths, with B. Schütz, N. Aschenbruck, S. Bussmann and M. Juhnke-Kubitzke, Proc. of the 45th IEEE LCN Symposium on Emerging Topics in Networking LCN, virtually hosted in Sydney, Australia, Nov. 16–19, 2020.
  • Stationarity for the Small World in Motion Mobility Model, with Nils Aschenbruck, Christian Heiden und Matthias Schwamborn, MSWIM '19: Proceedings of the 22nd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, Nov 25-29, 2019, https://doi.org/10.1145/3345768.3355935
  • Crossing Numbers and Stress of Random Graphs, with Markus Chimani and Matthias Reitzner, In Proceedings 26th International Symposium, GD 2018, Barcelona, Spain, 255--268, 2018 available here and for an extended journal version here: https://arxiv.org/abs/1808.07558
  • Fluctuations in a general preferential attachment model via Stein's method, with Carina Betken and Marcel Ortgiese, Random Structures & algorithms, vol.55, no.4, 2019 available here
  • Connection times in large ad-hoc mobile networks, Bernoulli, vol.22, no.4, 2143--2176, 2016 available here
    with Gabriel Faraud, Wolfgang König
  • The random disc thrower problem, Proceedings of the 90th European Study Group Mathematics with Industry, 59-78, 2013  available here with T. van der Aalst, D. Denteneer, M. Hong Duong, R. J. Kang, M. Keane, J. Kool, I. Kryven, T. Meyfroyt, T. Müller, G. Regts, J. Tomczyk
  • Edge fluctuations of eigenvalues of Wigner matrices, High Dimensional Probability VI: the Banff volume, Progress in Probability, vol.66, 261-275, Springer, Basel, 2013 available here
    with Peter Eichelsbacher
  • Moderate deviations for the determinant of Wigner matrices, Dedicated to Friedrich Götze on the occasion of his sixtieth birthday, Limit Theorems in Probability, Statistics and Number Theory, Springer Proceedings in Mathematics & Statistics, vol.42, 253-275, 2013, available here
    with Peter Eichelsbacher
  • Moderate deviations for the eigenvalue counting function of Wigner matrices, ALEA, Lat. Am. J. Probab. Math. Stat. 10 (1), 27-44, 2013, available here
    with Peter Eichelsbacher
  • Moderate deviations via cumulants, Journal of Theor. Probability, 2012, available here
    with Peter Eichelsbacher
  • Moments of recurrence times for Markov chains, Electronic Comm. Probab., 16(28), 296-303, 2011, available here
    with Frank Aurzada, Marcel Ortgiese, Michael Scheutzow
  • Moderate deviations in a random graph and for the spectrum of Bernoulli random matrices, Electronic Journal of Probability, Vol. 14, Paper no. 92, 2636-2656, 2009, available here
    with Peter Eichelsbacher
  • Perpendicular transport of charged particles in slab turbulence: recovery of diffusion for realistic wave-spectra?, Journal of Physics G: Nuclear and Particle Physics, 35, 025202, 2008
    with Andreas Shalchi
  • Velocity correlation functions of charged test particles, Journal of Physics G: Nuclear and Particle Physics, 34, 859, 2007
    with Andreas Shalchi

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