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ORCIDNICE 2020: Heidelberg, Germany
- Murat Okandan, James B. Aimone:
NICE '20: Neuro-inspired Computational Elements Workshop, Heidelberg, Germany, March 17-20, 2020. ACM 2020, ISBN 978-1-4503-7718-8Postponed due to the Covid-19 pandemic. - J. David Schaffer:
Evolving Spiking Neural Networks for Robot Sensory-motor Decision Tasks of Varying Difficulty. 1:1-1:7 - Catherine D. Schuman
, J. Parker Mitchell, Robert M. Patton, Thomas E. Potok, James S. Plank:
Evolutionary Optimization for Neuromorphic Systems. 2:1-2:9 - Craig M. Vineyard, Mark Plagge, Sam Green:
Comparing Neural Accelerators & Neuromorphic Architectures The False Idol of Operations. 3:1-3:6 - Johan Kwisthout, Nils Donselaar:
On the computational power and complexity of Spiking Neural Networks. 4:1-4:7 - Thomas Passer Jensen, S. Tata, Auke Jan Ijspeert, Silvia Tolu:
Adaptive control for hindlimb locomotion in a simulated mouse through temporal cerebellar learning. 5:1-5:8 - Bill Kay, Prasanna Date, Catherine D. Schuman:
Neuromorphic Graph Algorithms: Extracting Longest Shortest Paths and Minimum Spanning Trees. 6:1-6:6 - Johannes Leugering:
Making spiking neurons more succinct with multi-compartment models. 7:1-7:6 - J. Parker Mitchell, Catherine D. Schuman, Robert M. Patton, Thomas E. Potok:
Caspian: A Neuromorphic Development Platform. 8:1-8:6 - Dylan M. Paiton, Steven Shepard, Kwan Ho Ryan Chan, Bruno A. Olshausen:
Subspace Locally Competitive Algorithms. 9:1-9:8 - Tej Pandit, Dhireesha Kudithipudi:
Relational Neurogenesis for Lifelong Learning Agents. 10:1-10:9 - Jakob Jordan, Mihai A. Petrovici, Walter Senn, João Sacramento:
Conductance-based dendrites perform reliability-weighted opinion pooling. 11:1-11:3 - Alpha Renner, Forrest Sheldon, Anatoly Zlotnik, Louis Tao, Andrew T. Sornborger:
Implementing Backpropagation for Learning on Neuromorphic Spiking Hardware. 12:1-12:3 - Younes Bouhadjar, Markus Diesmann, Dirk J. Wouters, Tom Tetzlaff:
The speed of sequence processing in biological neuronal networks. 13:1-13:2 - Julian Göltz, Andreas Baumbach, Sebastian Billaudelle, Ákos F. Kungl, Oliver Breitwieser, Karlheinz Meier, Johannes Schemmel, Laura Kriener, Mihai A. Petrovici:
Fast and deep neuromorphic learning with first-spike coding. 14:1-14:3 - Elena Kreutzer, Mihai A. Petrovici, Walter Senn:
Natural gradient learning for spiking neurons. 15:1-15:3 - Christoph Ostrau, Christian Klarhorst, Michael Thies, Ulrich Rückert:
Benchmarking of Neuromorphic Hardware Systems. 16:1-16:4 - Korbinian Schreiber, Timo C. Wunderlich, Christian Pehle, Mihai A. Petrovici, Johannes Schemmel, Karlheinz Meier:
Closed-loop experiments on the BrainScaleS-2 architecture. 17:1-17:3 - Florian Kelber, Binyi Wu, Bernhard Vogginger, Johannes Partzsch, Chen Liu, Marco Stolba, Christian Mayr:
Mapping Deep Neural Networks on SpiNNaker2. 18:1-18:3 - Forrest Sheldon, Francesco Caravelli:
The Computational Capacity of Mem-LRC Reservoirs. 19:1-19:4 - Guangzhi Tang, Konstantinos P. Michmizos:
Real-time Mapping on a Neuromorphic Processor. 20:1-20:3 - Tarek M. Taha, Chris Yakopcic, Nayim Rahman, Tanvir Atahary, Scott Douglass:
Cognitive Domain Ontologies: HPCs to Ultra Low Power Neuromorphic Platforms. 21:1-21:3 - Christopher H. Bennett, Ryan Dellana, T. Patrick Xiao, Ben Feinberg, Sapan Agarwal, Suma Cardwell, Matthew J. Marinella, William Severa, Brad Aimone:
Evaluating complexity and resilience trade-offs in emerging memory inference machines. 22:1-22:4 - Edward Paxon Frady, Garrick Orchard, David Florey, Nabil Imam, Ruokun Liu, Joyesh Mishra, Jonathan Tse, Andreas Wild, Friedrich T. Sommer, Mike Davies:
Neuromorphic Nearest Neighbor Search Using Intel's Pohoiki Springs. 23:1-23:10 - John V. Monaco, Ryad Benosman:
General Purpose Computation with Spiking Neural Networks: Programming, Design Principles, and Patterns. 24:1-24:9
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