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")

Agenda as .pdf download

The agenda as of 11 April 2023 can be downloaded here as .pdf.

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.

Also available: a schematic view as .pdf

Registration

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

08:00‑08:30
(30 min)
 Registration, coffee
08:30
Session chair: Dhireesha Kudithipudi
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. Suma George Cardwell, National Laboratories
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)
 How Unsupervised Learning During Sleep Could Contribute to Temporal Pattern Recognition and The Gain of InsightItamar 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

(Unfortunately no slides were in the talk video capture - therefore there is no video of the talk available here)

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.

(Unfortunately no slides were in the talk video capture - therefore there is no video of the talk available here)

show abstract

Denis Kleyko (RISE)
12:30‑13:30
(60 min)
lunch
13:30
Session chair: Johannes Schemmel
13:30‑13:55
(25+5 min)
 Full-stack Co-Design for Neuromorphic Systems
show talk video

(this talk video has a gap)

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 SpiNNaker2
show talk video
Christian 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
show talk video

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
show talk video

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
show talk video

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)
 (break)
18:00‑18:30
(30 min)
 Shuttle service to downtown area

Shuttle leaves at 18:00h from the meeting place and goes to "UTSA, San Pedro 1" (place of the welcome reception)

18:30‑20:00
(90 min)
 Welcome reception in San Antonio downtown, at UTSA, San Pedro 1, 1st floor lobby

Address of the place: 506 Dolorosa St, San Antonio, TX 78204

(For people using their own car: parking space should likely be available at "Dolorosa Lot")

20:00‑21:00
(60 min)
 1h to explore San Antonio downtown (self guided)
21:00‑21:30
(30 min)
 Shuttle back to UTSA

Shuttle leaves at 21:00h = 9:00 pm and returns to "UTSA main campus" (conference venue)


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

("Hardware" day)

08:00‑08:30
(30 min)
 Breakfast
08:30
Session chair: Suma George Cardwell
08:30‑09:15
(45+5 min)
 Keynote: Versatility, Efficiency, and Resilience in Large-Scale Neuromorphic Intelligence at the Edge
show talk video

show abstract

Gert Cauwenberghs (UC San Diego)
09:20‑09:45
(25+5 min)
 All Aboard the Open-Source Neuromorphic Hardware Hype Train
show talk video

show abstract

Jason Eshraghian (University of California, Santa Cruz)
09:50‑10:15
(25+5 min)
 Exploring Information-Theoretic Criteria to Accelerate the Tuning of Neuromorphic Level-Crossing ADCs
video (restricted access)

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

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)
 Structure-function duality in memristive intelligent systems
show talk video

show abstract

Melika Payvand (Institute of Neuroinformatics, ETH Zurich and University of 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 (Robotics Royal College of Art (UK))
11:50‑12:15
(25 min)
 Poster flash talks: 1 min appetizer for posters
12:15‑12:20
(5 min)
 Group photo

12:20‑13:45
(85 min)
Poster-Lunch (posters + finger food)
13:45
Session chair: Catherine Schuman
13:45‑14:10
(25+5 min)
 hxtorch.snn: Machine-learning-inspired Spiking Neural Network Modeling on BrainScaleS-2
show talk video

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)
 SupportHDC: Hyperdimensional Computing with Scalable Hypervector Sparsity
show talk video

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

show abstract

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
17:30‑19:00
(90 min)
 Break
19:00‑21:00
(120 min)
Conference dinner

Location: iH-E-B Ballroom 1.104


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

("Applications day")

08:00‑08:30
(30 min)
 Breakfast
08:30
Session chair: Craig Michael Vineyard
08:30‑09:15
(45+5 min)
 Exciting Opportunities at the Intersection of Spatial Neuroscience, Robot Navigation, and Neuromorphic Compute and Sensing
show talk video
Michael Milford (QUT Robotics Centre)
09:20‑09:30
(10+5 min)
 Demonstration of neuromorphic sequence learning on a memristive array
show talk video

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 - with the funders attending via video
  • Joe Hays (U.S Naval research Lab)
  • Andrey Kanaev (NSF)
  • Tina Kaarsberg (DOE)
  • Jano Costard (SPRIN-D, Germany)
  • Clare Thiem (AFRL)
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.

(unfrotunately no talk video captured)

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.

(unfrotunately no talk video captured)

Diego Chavez Arana (talk presented by Andrew Sornborger) (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.

(unfrotunately no talk video captured)

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.

(unfrotunately no talk video captured)

George Brayshaw (University of Bristol)
12:35‑14:05
(90 min)
Poster-Lunch (posters + finger food)
14:05
Session chair: Felix Wang
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
show talk video

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

show abstract

Jens Pedersen (KTH Royal Institute of Technology)
14:50‑15:15
(25+5 min)
 NeuroBench: Advancing Neuromorphic Computing through Collaborative and Rigorous BenchmarkingVijay 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
show talk video

Authors: Wallace Lawson, Anthony Harrison and Greg Trafton.

Our autonomous robot, Bight, can be a reliable teammate that is capable of assisting in performing routine maintenance tasks on a Naval vessel. In this paper, we consider the task of maintaining the electrical panel. A vital first step is putting the robot into the correct position to view all of the parts of the electrical panel. The robot can get close, but the arm of the robot will need to move to where it can see everything. Here, we propose to solve this using a sigma delta spiking network that is trained using deep Q learning. Our approach is able to successfully solve this problem at varying distances. While we show how this works on this specific problem, we believe this approach to be general enough to be applied to any similar problem.

Ed Lawson (U.S Naval Research Lab)
16:20‑16:45
(25+5 min)
 Towards Neuromorphic Edge Intelligence
show talk video
Joseph Hays (U.S Naval research Lab)
16:50‑17:00
(10 min)
 Best paper award! (Sponsored by IOP neuroscience and APL machine learning)
17:00‑17:30
(30 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
  • Intel Loihi 2: Build more impactful neuromorphic applications with Intel Loihi 2 and the open-source Lava framework

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
Preparation: Best to get an EBRAINS account here) ahead of time. We can also create a guest-account on the spot.

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
Preparation: Please clone and install: https://github.com/snl-nerl/fugu

Intel Loihi 2: Build more impactful neuromorphic applications with Intel Loihi 2 and the open-source Lava framework

Tim Shea from Intel Labs will demonstrate how you can program applications using the open-source Lava framework for neuromorphic computing and how to compile and run those applications on Intel Loihi 2 hardware. Lava is an excellent platform for neuromorphic researchers seeking more real-world impact because the high-level, modular API makes it easy for other labs to replicate your work while the flexible compiler architecture makes it easy to distribute your models across conventional and neuromorphic hardware. In this tutorial, you will learn how to build and run several example applications in Lava, including a deep learning model, a Dynamic Neural Field algorithm, a mathematical optimizer.

Format: This tutorial will introduce application programming in Lava through a series of Jupyter notebook tutorials. Attendees can follow along building the applications on their own laptops or using any free cloud-based notebook (e.g. Google Colab). Each application can be run locally on a standard CPU and the presenter will demonstrate how to run the examples on an Intel Kapoho Point neuromorphic system. All the necessary code and instructions are available at github.com/lava-nc.

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

Room: Harris


Room: Mesquite


Room: Travis

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

Room: Harris


Room: Mesquite


Room: Travis

13:00‑14:00
(60 min)
 Lunch
14:00‑16:00
(120 min)
 Tutorial session 3 (tutorials in parallel)
N2ABrainScaleSIntel Loihi 2

Room: Harris


Room: Mesquite


Room: Travis

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