Show this page for printing or as short info (with end time)

NICE 2023 - Agenda

(show all abstracts)
Tuesday, 11 April 2023
08:00
NICE 2023 -- day 1

("Theory day")

Venue

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.

Registration

Please follow the link on the registration page to register for the workshop.

08:00‑08:30
(30 min)
 Registration, coffee
08:30‑08:35
(5+5 min)
 Welcome
08:40‑08:45
(5+5 min)
 Opening by Dr. Taylor Eighmy, President, University of Texas at San Antonio
08:50‑09:35
(45+5 min)
 Organisers round
  • Dr. Dhireesha Kudithipudi, UT San Antonio
  • Dr. Brad Aimone, Sandia National Laboratories
  • Dr. Johannes Schemmel, Kirchhoff-Institute for Physics, Heidelberg University
  • Dr. Winfried Wilcke, IBM
  • Dr. Yulia Sandamirskaya, Intel
09:40‑10:25
(45+5 min)
 Keynote: Neuroevolution: Beyond human design of neural networks

show abstract

Risto Mikkulainen (UT Austin)
10:30‑11:00
(30 min)
 Break
11:00‑11:25
(25+5 min)
 full: invited (T)Itamar Lerner (University of Texas at San Antonio)
11:30‑11:40
(10+5 min)
 AEStream: Accelerated event-based processing with coroutines

Authors: Jens Egholm Pedersen and Jörg Conradt.

show abstract

Jens Egholm Pedersen (KTH Royal Institute of Technology)
11:45‑12:10
(25+5 min)
 Goemans-Williamson MAXCUT approximation algorithm on Loihi

Authors: Bradley Theilman and James B. Aimone

Bradley Theilman (Sandia National Laboratories)
12:15‑12:25
(10+5 min)
 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.

show abstract

Denis Kleyko (RISE)
12:30‑13:30
(60 min)
 lunch
13:30‑13:55
(25+5 min)
 Full-stack Co-Design for Neuromorphic Systems

show abstract

Rajit Manohar (Yale University)
14:00‑14:25
(25+5 min)
 Modeling Coordinate Transformations in the Dragonfly Nervous System

Authors: Claire Plunkett and Frances Chance.

show abstract

Claire Plunkett (Sandia National Laboratories)
14:30‑14:55
(25+5 min)
 Beyond Neuromorphics: Non-Cognitive Applications of SpiNNaker2Christian Mayr (TU Dresden)
15:00‑15:30
(30 min)
 break
15:30‑15:40
(10+5 min)
 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)
15:45‑16:10
(25+5 min)
 NEO: Neuron State Dependent Mechanisms for Efficient Continual Learning

Authors: Anurag Daram and Dhireesha Kudithipudi.

show abstract

Anurag Daram (UTSA)
16:15‑16:25
(10+5 min)
 Impact of Noisy Input on Evolved Spiking Neural Networks for Neuromorphic Systems

Authors: Karan Patel and Catherine Schuman.

Karan Patel (University of Tennessee Knoxville)
16:30‑16:35
(5 min)
 Spotlight: Intel Neuromorphic Deep Noise Suppression Challenge
16:35‑17:30
(55 min)
 Open mic / discussions
17:30
End of the first day of NICE
17:30‑18:00
(30 min)
 (self organised travel to San Antonio downtown)
18:00‑20:30
(150 min)
 Welcome reception in San Antonio downtown

(Travel on your own)


Wednesday, 12 April 2023
08:00
NICE 2023 - day 2

("Hardware" day)

08:00‑08:30
(30 min)
 Breakfast
08:30‑09:15
(45+5 min)
 Keynote: Versatility, Efficiency, and Resilience in Large-Scale Neuromorphic Intelligence at the Edge

show abstract

Gert Cauwenberghs (UC San Diego)
09:20‑09:45
(25+5 min)
 full invited (H)Jason K Eshraghian (University of California, Santa Cruz)
09:50‑10:15
(25+5 min)
 SupportHDC: Hyperdimensional Computing with Scalable Hypervector Sparsity

Authors: Ali Safa, Ilja Ocket, Francky Catthoor and Georges Gielen.

show abstract

Ali Safa (Katholieke Universiteit Leuven)
10:20‑10:50
(30 min)
 break
10:50‑11:00
(10+5 min)
 Easy and efficient spike-based Machine Learning with mlGeNN

Authors: James Knight and Thomas Nowotny.

show abstract

James Knight (University of Sussex)
11:05‑11:30
(25+5 min)
 Beyond MVM applications for RRAMs in Spiking Neural Network HardwareMelika Payvand (Institute of Neuroinformatics, ETH Zurich)
11:35‑11:45
(10+5 min)
 Additive manufacture of polymeric organometallic ferroelectric diodes (POMFeDs) for structural neuromorphic hardware

Author: Davin Browner.

show abstract

Davin Browner
11:50‑12:15
(25 min)
 Poster flash talks: 1 min appetizer for posters
12:15‑13:45
(90 min)
 Poster-Lunch (posters + finger food)
13:45‑14:10
(25+5 min)
 hxtorch.snn: Machine-learning-inspired Spiking Neural Network Modeling on BrainScaleS-2

Authors: Philipp Spilger, Elias Arnold, Luca Blessing, Christian Mauch, Christian Pehle, Eric Müller and Johannes Schemmel.

show abstract

Philipp Spilger (Heidelberg University)
14:15‑14:40
(25+5 min)
 Exploring Information-Theoretic Criteria to Accelerate the Tuning of Neuromorphic Level-Crossing ADCs

Authors: Ali Safa, Jonah Van Assche, Charlotte Frenkel, André Bourdoux, Francky Catthoor and Georges Gielen.

Ali Safa (Katholieke Universiteit Leuven)
14:45‑15:15
(30 min)
 break
15:15‑15:40
(25+5 min)
 Accelerating AI with analog in-memory computing

show abstract

Stefano Ambrogio (IBM)
15:45‑15:55
(10+5 min)
 Configurable Activation Functions based on DW-MTJ LIF Neurons

Authors: Wesley Brigner, Naimul Hassan, Xuan Hu, Christopher Bennett, Felipe Garcia-Sanchez, Can Cui, Alvaro Velasquez, Matthew Marinella, Jean Anne Incorvia and Joseph S. Friedman.

Wesley Brigner (University of Texas Dallas)
16:00‑16:25
(25+5 min)
 Shunting Inhibition as a Neural-Inspired Mechanism for Multiplication in Neuromorphic Architectures

Authors: Frances Chance and Suma Cardwell.

show abstract

Frances Chance (Sandia National Lab)
16:30‑17:30
(60 min)
 Open mic / discussions
19:00‑21:00
(120 min)
 Conference dinner

Thursday, 13 April 2023
08:00
NICE 2023 - day 3

("Applications day")

08:00‑08:30
(30 min)
 Breakfast
08:30‑09:15
(45+5 min)
 Keynote (A)Michael Milford (QUT Robotics Centre)
09:20‑09:30
(10+5 min)
 Demonstration of neuromorphic sequence learning on a memristive array

Authors: Sebastian Siegel, Tobias Ziegler, Younes Bouhadjar, Tom Tetzlaff, Rainer Waser, Regina Dittmann and Dirk Wouter.

show abstract

Sebastian Siegel (Peter Grünberg Institute, Forschungszentrum Jülich)
09:35‑10:35
(60 min)
 Funders panel (TBC)
10:35‑11:05
(30 min)
 Break
11:05‑11:30
(25+5 min)
 Speech2Spikes: Efficient Audio Encoding Pipeline for Real-time Neuromorphic Systems

Authors: Kenneth Stewart, Timothy Shea, Noah Pacik-Nelson, Eric Gallo and Andreea Danielescu.

show abstract

Kenneth Stewart (University of California, Irvine)
11:35‑11:45
(10+5 min)
 Spiking LCA in a Neural Circuit with Dictionary Learning and Synaptic Normalization

Authors: Diego Chavez Arana, Alpha Renner and Andrew Sornborger.

Diego Chavez Arana, (Los Alamos National Lab)
11:50‑12:15
(25+5 min)
 Neuromorphic Downsampling of Event-Based Camera Output

Authors: Charles Rizzo, Catherine Schuman and James Plank.

show abstract

Charles Rizzo (University of Tennessee Knoxville)
12:20‑12:30
(10+5 min)
 A Neuromorphic System for Real-time Tactile Texture Classification

Authors: George Brayshaw, Martin Pearson and Benjamin Ward-Cherrier.

George Brayshaw (University of Bristol)
12:35‑14:05
(90 min)
 Poster-Lunch (posters + finger food)
14:05‑14:15
(10+5 min)
 SIFT-ONN: SIFT Feature Detection Algorithm Employing ONNs for Edge Detection

Authors: Madeleine Abernot, Sylvain Gauthier, Théophile Gonos and Aida Todri-Sanial.

Madeleine Abernot (University of Montpellier)
14:20‑14:45
(25+5 min)
 Translation and Scale Invariance for Event-Based Object tracking

Authors: Jens Egholm Pedersen, Raghav Singhal and Jörg Conradt.

We propose a new method to accurately predict spatial coordinates of objects from event data using spiking neurons without temporal averaging. Our method achieves accuracies comparable to artificial neural networks, demonstrates faster convergence, and is directly portable to neuromorphic hardware. In this talk, we will present our model, along with unpublished experimental data, and discuss its generalization to real-life settings. github.com/jegp/coordinate-regression/

Jens Egholm Pedersen (KTH Royal Institute of Technology)
14:50‑15:15
(25+5 min)
 full invited (A)invited speaker: Vijay Janapa Reddi (Harvard University)
15:20‑15:50
(30 min)
 break
15:50‑16:15
(25+5 min)
 Sigma-Delta networks for Robot Arm Control

Authors: Wallace Lawson, Anthony Harrison and Greg Trafton.

show abstract

Wallace Lawson (U.S Naval Research Lab)
16:20‑16:45
(25+5 min)
 full invited (A)invited speaker: Joe Hays (U.S Naval research Lab)
16:50‑17:30
(40 min)
 Open mic / discussions
17:30
End of day 3 and of the talk-days of NICE 2023

Friday, 14 April 2023
08:00
NICE 2023: hands-on tutorials day

Likely three slots in parallel

Confirmed tutorials:

  • An Introduction to a Simulator for Super Conducting Optoelectronic Networks (Sim-SOENs)
  • Sandia – Fugu Introductory Tutorial (offered twice with the same content)
  • N2A -- An IDE for neural modeling
  • Hands-on BrainScaleS - analog accelerated neuromorphic compute hardware (The hands-on session is offered twice with the same content). The BrainScaleS hardware systems are available for use online
  • to be confirmed: Intel Loihi tutorial

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.
Format: Examples and instructions will be given in the form of Jupyter Notebook tutorials (already well into development). If it is conducive to the conference environment, these notebooks may be available for download and use in real-time. If this latter format is the case, practice exercises can be derived for active learning.

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.
Format: The first hour will provide a general introduction to the integrated development environment (IDE) and cover basic use cases: model editing, running a simulation, sharing models via Git, and running parameter sweeps. The second hour will cover the basic LIF class hierarchy, techniques for designing your own component set, and integration with Sandia's Fugu tool.
Special Requirements: This will be a hands-on tutorial. N2A may be downloaded from https://github.com/frothga/n2a and run on your personal laptop.

BrainScaleS

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.
For using the BrainScaleS system during the tutorial (and also independently of the tutorial for own research, free of charge for evaluation) an EBRAINS account (also free of charge) is needed (get an EBRAINS account here).
More info on how to get started using BrainScaleS.
Format: Introductory presentation, followed by interactive hands-on tutorials. The attendants of the tutorial can a webbrowser on their own laptops to execute and change provided tutorials and explore on their own. Attendants will be able to continue accessing the systems with a generous test-quota also after the 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.
Format: Interactive

08:00‑08:30
(30 min)
 Breakfast
08:30‑10:30
(120 min)
 Tutorial session 1 (tutorials in parallel)
Sim-SOENsFuguBrainScaleS



10:30‑11:00
(30 min)
 Break
11:00‑13:00
(120 min)
 Tutorial session 2 (tutorials in parallel)
N2AFugu


13:00‑14:00
(60 min)
 Lunch
14:00‑16:00
(120 min)
 Tutorial session 3 (tutorials in parallel)
N2ABrainScaleS


16:00‑16:30
(30 min)
 Farewell coffee
16:30
End of the tutorial day