NICE 2023 - Agenda(show all abstracts)
|Tuesday, 11 April 2023|
|08:00||NICE 2023 -- day 1|
UTSA Student Union, H-E-B University Center, 1 UTSA Circle, San Antonio, TX 78249, Texas, United States of America.show a map of the venue.
Please follow the link on the registration page to register for the workshop.
|Opening by Dr. Taylor Eighmy, President, University of Texas at San Antonio|
|Keynote: Neuroevolution: Beyond human design of neural networks||Risto Mikkulainen (UT Austin)|
|full: invited (T)||Itamar Lerner (University of Texas at San Antonio)|
|AEStream: Accelerated event-based processing with coroutines|
Authors: Jens Egholm Pedersen and Jörg Conradt.
|Jens Egholm Pedersen (KTH Royal Institute of Technology)|
|Goemans-Williamson MAXCUT approximation algorithm on Loihi|
Authors: Bradley Theilman and James B. Aimone
|Bradley Theilman (Sandia National Laboratories)|
|Work in Progress: A Network of Sigma–Pi Units producing Higher-order Interactions for Reservoir Computing|
Authros: Denis Kleyko, Christopher Kymn, Bruno A. Olshausen, Friedrich T. Sommer and E. Paxon Frady.
|Denis Kleyko (RISE)|
|Full-stack Co-Design for Neuromorphic Systems||Rajit Manohar (Yale University)|
|Modeling Coordinate Transformations in the Dragonfly Nervous System|
Authors: Claire Plunkett and Frances Chance.
|Claire Plunkett (Sandia National Laboratories)|
|Beyond Neuromorphics: Non-Cognitive Applications of SpiNNaker2||Christian Mayr (TU Dresden)|
|Online training of quantized weights on neuromorphic hardware with multiplexed gradient descent|
Authros: Adam McCaughan, Cory Merkel, Bakhrom Oripov, Andrew Dienstfrey, Sae Woo Nam and Sonia Buckley.
|Adam McCaughan (NIST)|
|NEO: Neuron State Dependent Mechanisms for Efficient Continual Learning|
Authors: Anurag Daram and Dhireesha Kudithipudi.
|Anurag Daram (UTSA)|
|Impact of Noisy Input on Evolved Spiking Neural Networks for Neuromorphic Systems|
Authors: Karan Patel and Catherine Schuman.
|Karan Patel (University of Tennessee Knoxville)|
|Spotlight: Intel Neuromorphic Deep Noise Suppression Challenge|
|Open mic / discussions|
|17:30||End of the first day of NICE|
|(self organised travel to San Antonio downtown)|
|Welcome reception in San Antonio downtown |
(Travel on your own)
|Friday, 14 April 2023|
|08:00||NICE 2023: hands-on tutorials day|
Likely three slots in parallel
An Introduction to a Simulator for Super Conducting Optoelectronic Networks (Sim-SOENs)
This tutorial will suffice to impart a functional understanding of Sim-SOENs. Starting with the computational building blocks of SOEN neurons, we will cover the nuances and processing power of single dendrites, before building up to dendritic arbors within complex neuron structures. We will find it is straightforward to implement arbitrary neuron structures and even dendritic-based logic operations. Even at this single neuron level, we will already demonstrate efficacy on basic computational tasks. From there we will scale to network simulations of many-neuron systems, again with demonstrative use-cases. By the end of the tutorial, participants should be able to easily generate custom SOEN neuron structures and networks. These lessons will apply directly to researching in the computational paradigm that is to be instantiating on the burgeoning hardware of SOENs.
N2A -- An IDE for neural modeling
N2A is a tool for editing and simulating large-scale/complex neural models. These are written in a simple equation language with object-oriented features that support component creation and reuse. The tool compiles these models for various hardware targets ranging from neuromophic devices to supercomputers.
A hands-on tutorial for online interactive use of the BrainScaleS neuromorphic compute system: from the first log-in via the EBRAINS Collaboratory to interactive emulation of small spiking neural networks. This hands-on tutorial is especially suitable for beginners (more advanced attendants are welcome as well). We are going to use the BrainScaleS tutorial notebooks for this event.
Fugu Introductory Tutorial
The tutorial will cover the basic design and practice of Fugu, a software package for composing spiking neural algorithms. We will begin will an introductory presentation on the motivation, design, and limitations of Fugu. Then, we will do two deep dive, interactive tutorials using jupyter notebooks. The first will cover how to use Fugu with pre-existing components, we call Bricks. The second will cover how to build a custom brick to perform a particular algorithm. In this case, the algorithm we choose will be an 80-20 network.
|Tutorial session 1 (tutorials in parallel)|
|Tutorial session 2 (tutorials in parallel)|
|Tutorial session 3 (tutorials in parallel)|
|16:30||End of the tutorial day|