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)
Inductive bias transfer between brains and machines
Machine Learning, in particular computer vision, has made tremendous progress in recent year. On standardized datasets deep networks now frequently achieve close to human or super human performance. However, despite this enormous progress, artificial neural networks still lag behind brains in their ability to generalize to new situations. Given identical training data, differences in generalization are caused by many defining features of a learning algorithm, such as network architecture and learning rule. Their joint effect, called ‘‘inductive bias,’’ determines how well any learning algorithm—or brain—generalizes: robust generalization needs good inductive biases. Artificial networks use rather nonspecific biases and often latch onto patterns that are only informative about the statistics of the training data but may not generalize to different scenarios. Brains, on the other hand, generalize across comparatively drastic changes in the sensory input all the time. I will give an overview on some conceptual ideas and preliminary results how the rapid increase of neuroscientific data could be used to transfer low level inductive biases from the brain to learning machines.
Fabian Sinz
17:00‑17:45 (45 min)
Open mic / discussion
18:00‑21:00 (180 min)
Conference dinner
Thursday, 19 March 2020
08:45
NICE 2020, workshop day III -- NOTE: NICE will be postponed!
09:00‑09:15 (15 min)
Welcome / overview
09:15‑09:55 (40+5 min)
Keynote: Bottom-up and top-down neuromorphic processor design: Unveiling roads to embedded cognition
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).