6th March 2020: We are sorry to announce that NICE 2020, scheduled to be held on March 17-20 2020, will be postponed to a later date. Please see here for the new date in March 2021
NEUROTECH event: Future Application Directions for Neuromorphic Computing Technologies: agenda and registration (free, but mandatory). A half-day event with special focus on potential application of neuromorphic computing.
Travel info:
Getting to the venue:
the nearest tram stop to the meeting venue is "Heidelberg Bunsengymnasium" (marked in the map linked above) [online timetable]https://reiseauskunft.bahn.de//bin/query.exe/en?Z=Neuenheim+Bunsengymnasium,+Heidelberg), provided by German Railway. Here you can also buy tickets online
via Railway from the train station directly attached to the airport "Frankfurt Flughafen Fernbahnhof": online timetable by German Railway (tickets are also sold online via this website)
via airport shuttle service directly to the hotel. We have good experience with TLS Heidelberg. A single, shared ride costs about 40 Euro / person / ride
Hotels:
These hotels are relatively close to the meeting venue (Kirchhoff-Institute for Physics, see the map above). A lot more hotels are listed in online hotel booking sites (e.g. on booking.com)
Thomas Passer Jensen (Technical University of Denmark)
17:10‑17:55 (45 min)
Open mic / discussions
19:00‑21:30 (150 min)
Poster dinner
The max. poster size is A0, orientation PORTRAIT (841 mm wide x 1189 mm high)
Wednesday, 18 March 2020
08:45
NICE 2020, workshpo day II -- NOTE: NICE will be postponed!
09:00‑09:15 (15 min)
Welcome / overview
09:15‑09:55 (40+5 min)
Keynote
Wolfgang Maass
10:00‑10:20 (20+5 min)
On the computational power and complexity of Spiking Neural Networks
Johan Kwisthout and Nils Donselaar
The last decade has seen the rise of neuromorphic architectures based on artificial spiking neural networks, such as the SpiNNaker,
TrueNorth, and Loihi systems. The massive parallelism and co-locating of computation and memory in these architectures potentially allows for an energy usage that is orders of magnitude lower compared to traditional Von Neumann architectures.
However, to date a comparison with more traditional computational architectures (particularly with respect to energy usage) is hampered by the lack of a formal machine model and a computational complexity theory for neuromorphic computation. In this paper we take the first steps towards such a theory. We introduce spiking neural networks as a machine model where — in contrast to the familiar Turing machine — information and the manipulation thereof are co-located in the machine. We introduce canonical problems, define hierarchies of complexity classes and provide some first completeness results.
(Nils Donselaar)
10:25‑10:45 (20+5 min)
The speed of sequence processing in biological neuronal networks
NICE 2020, Tutorials day: NOTE: NICE will be POSTPONED!
The tutorial day can be booked as one of the registration options. On the tutorial day hands-on interactive tutorials with several different neuromorphic compute systems will be offered:
Intel Loihi platform tutorial (Lecture style. To follow along from your own laptop your need to engage with Intel’s Intel’s Neuromorphic Research Community beforehand (email inrc_interest@intel.com for more information).