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BEGIN:DAYLIGHT
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20230521
DTEND;VALUE=DATE:20230526
DTSTAMP:20260416T150919
CREATED:20230129T222609Z
LAST-MODIFIED:20230129T222609Z
UID:10000024-1684627200-1685059199@www.neuropac.info
SUMMARY:International Symposium on Circuits and Systems (ISCAS) 2023
DESCRIPTION:The IEEE International Symposium on Circuits and Systems (ISCAS) is the flagship conference of the IEEE Circuits and Systems (CAS) Society and the world’s premiere forum for researchers in the active fields of theory\, design and implementation of circuits and systems.
URL:https://www.neuropac.info/event/international-symposium-on-circuits-and-systems-iscas-2023/
LOCATION:Monterey\, Monterey\, CA\, United States
CATEGORIES:Conference
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20230518T163000
DTEND;TZID=UTC:20230518T173000
DTSTAMP:20260416T150919
CREATED:20230127T222256Z
LAST-MODIFIED:20230828T170621Z
UID:10000043-1684427400-1684431000@www.neuropac.info
SUMMARY:Theory of Neuromorphic Computing
DESCRIPTION:Recurring discussion meeting by researchers interested in the theory of neuromorphic computing. \nHosted by Arne Diehl and Johan Kwisthout of Radboud University. To join the meetings\, please contact Arne Diehl: arne.diehl@donders.ru.nl.
URL:https://www.neuropac.info/event/theory-of-neuromorphic-computing/2023-05-18/
LOCATION:Online
CATEGORIES:Discussion
ORGANIZER;CN="Arne Diehl":MAILTO:arne.diehl@donders.ru.nl
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230509T080000
DTEND;TZID=America/Los_Angeles:20230509T090000
DTSTAMP:20260416T150919
CREATED:20230509T065534Z
LAST-MODIFIED:20230509T065534Z
UID:10000234-1683619200-1683622800@www.neuropac.info
SUMMARY:INRC Forum: Bradley Theilman
DESCRIPTION:Stochastic Neuromorphic Circuits for Solving MAXCUT\nAbstract: Finding the maximum cut of a graph (MAXCUT) is a classic optimization problem that has motivated parallel algorithm development. In this talk\, I will present two neuromorphic circuits that transform a source of randomness into computationally useful correlations for approximating solutions to graph MAXCUT. Neuromorphic computing has been successfully applied to various graph algorithms\, by exploiting the analogy between a graph and the connectivity of a neural circuit. However\, the physical constraints of neuromorphic hardware make translating an arbitrary graph into the neuromorphic domain challenging. Neuromorphic computing is also beginning to explore stochastic devices as efficient sources of randomness for large-scale stochastic algorithms. Graph MAXCUT is a well-known NP-complete discrete optimization problem with the best-known approximate solutions being stochastic algorithms\, such as the Goemans-Williamson algorithm. I will show how to combine large-scale sources of intrinsic randomness with neuromorphic principles to implement two classes of stochastic approximations to graph MAXCUT in neuromorphic hardware. These approaches have architectural advantages over other neuromorphic graph algorithms and benefit from the theoretical performance guarantees of their algorithmic inspirations. I will show results from simulations of these circuits as well as results from an implementation of one of these circuits on Intel’s Loihi neuromorphic system. This work opens a new direction for stochastic neuromorphic circuits applied to discrete optimization. \nBio: Bradley Theilman is a postdoctoral appointee at Sandia National Laboratories. His research focuses on applying neuroscientific principles to neuromorphic computing. He earned a Ph.D. in computational neuroscience in 2021 from UC San Diego\, where he worked on topological approaches to understanding neural population activity in the auditory regions of songbird brains in the laboratory of Dr. Tim Gentner. \nFor the meeting link\, see the full INRC Forum Spring 2023 Schedule (accessible only to INRC Affiliates and Fully Engaged Members).
URL:https://www.neuropac.info/event/inrc-forum-bradley-theilman/
LOCATION:Online
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230505T110000
DTEND;TZID=America/New_York:20230505T120000
DTSTAMP:20260416T150919
CREATED:20230423T184025Z
LAST-MODIFIED:20230423T185121Z
UID:10000232-1683284400-1683288000@www.neuropac.info
SUMMARY:Frances Chance - Modeling Coordinate Transformations in Neural and Neuromorphic Systems
DESCRIPTION:Hosted by the Perception and Robotics Group Seminar Series on Robotics and Computer Vision at the University of Maryland. \nAbstract. Animals excel at a wide range behaviors\, many of which are essential for survival. For example\, dragonflies are aerial predators\, known for both their speed and high success rate\, that must perform fast\, accurate\, and efficient calculations to survive. I will present a neural network model\, inspired by the dragonfly nervous system\, that calculates turning for successful prey interception. The model relies upon a coordinate transformation from eye-coordinates to body-coordinates\, an operation that must be performed by almost any animal nervous system relying upon sensory information to interact with the external world. I will discuss how I and collaborators are combining neuroscience experiments\, modeling studies\, and exploration of neuromorphic architectures to understand how the biological dragonfly nervous system performs coordinate transformations and to develop novel approaches for efficient neural- inspired computation. \nBio. As a computational neuroscientist\, Frances Chance has always been fascinated by how neural circuits compute information. Her current research focuses on applying knowledge of how neural systems operate towards the development of novel neuro-inspired algorithms and brain- based architectures. Frances Chance received her PhD and MS from Brandeis University and her BS from the California Institute of Technology. Currently she is a Principal Member of the Technical Staff at Sandia National Laboratories.
URL:https://www.neuropac.info/event/frances-chance-modeling-coordinate-transformations-in-neural-and-neuromorphic-systems/
LOCATION:University of Maryland\, 8125 Paint Branch Dr (Room IRB 4105)\, College Park\, MD\, 20740\, United States
CATEGORIES:Talk
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20230504T163000
DTEND;TZID=UTC:20230504T173000
DTSTAMP:20260416T150919
CREATED:20230127T222256Z
LAST-MODIFIED:20230828T170621Z
UID:10000042-1683217800-1683221400@www.neuropac.info
SUMMARY:Theory of Neuromorphic Computing
DESCRIPTION:Recurring discussion meeting by researchers interested in the theory of neuromorphic computing. \nHosted by Arne Diehl and Johan Kwisthout of Radboud University. To join the meetings\, please contact Arne Diehl: arne.diehl@donders.ru.nl.
URL:https://www.neuropac.info/event/theory-of-neuromorphic-computing/2023-05-04/
LOCATION:Online
CATEGORIES:Discussion
ORGANIZER;CN="Arne Diehl":MAILTO:arne.diehl@donders.ru.nl
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230502T080000
DTEND;TZID=America/Los_Angeles:20230502T090000
DTSTAMP:20260416T150919
CREATED:20230430T102520Z
LAST-MODIFIED:20230430T102520Z
UID:10000233-1683014400-1683018000@www.neuropac.info
SUMMARY:INRC Forum: Jeff Orchard
DESCRIPTION:Hyperdimensional Algorithms using Spiking Phasors\nAbstract: Hyperdimensional (HD) computing offers a powerful framework for representing compositional reasoning. Such algorithms lend themselves to neural-network implementations\, allowing us to create neural networks that can perform cognitive functions\, like spatial reasoning\, arithmetic\, and symbolic logic. But the vectors involved can be quite large. Advances in neuromorphic hardware hold the promise of reducing the running time and energy footprint of neural networks by orders of magnitude. In this talk\, I will extend some pioneering work to run HD algorithms on a substrate of spiking neurons\, implementing examples in spatial memory\, function representation\, and temporal memory. \nBio: Jeff Orchard received degrees in applied mathematics from the University of Waterloo (BMath) and the University of British Columbia (MSc)\, and received his PhD in Computing Science from Simon Fraser University in 2003. Since then\, he has been a faculty member at the Cheriton School of Computer Science at the University of Waterloo in Canada. Prof. Orchard’s research focuses on computational neuroscience\, using mathematical models and computer simulations of neural networks in an effort to understand how the brain works. Guided by both theory and anatomy\, he is building neural networks based on computational theories of the brain — such as predictive coding — to uncover the way we perceive the world. His research also includes Vector Symbolic Architectures and Algebras\, spatial navigation\, and population coding. He is a core member of the Centre for Theoretical Neuroscience. \nFor the meeting link\, see the full INRC Forum Spring 2023 Schedule (accessible only to INRC Affiliates and Fully Engaged Members).
URL:https://www.neuropac.info/event/inrc-forum-jeff-orchard/
LOCATION:Online
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230501
DTEND;VALUE=DATE:20230506
DTSTAMP:20260416T150919
CREATED:20230129T222127Z
LAST-MODIFIED:20230129T222127Z
UID:10000022-1682899200-1683331199@www.neuropac.info
SUMMARY:International Conference on Learning Representations (ICLR) 2023
DESCRIPTION:
URL:https://www.neuropac.info/event/international-conference-on-learning-representations-iclr-2023/
LOCATION:Kigali Convention Center\, Kigali\, Rwanda
CATEGORIES:Conference
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230430
DTEND;VALUE=DATE:20230515
DTSTAMP:20260416T150919
CREATED:20230127T225007Z
LAST-MODIFIED:20230127T225007Z
UID:10000011-1682812800-1684108799@www.neuropac.info
SUMMARY:CapoCaccia Workshop 2023
DESCRIPTION:Workshop theme for 2023: “Lessons from machine learning and neuroscience for building efficient intelligent systems” \nIt is an exciting era of significant progress in the quest for implementing intelligence in artificial systems. This stems from major breakthroughs in our understanding of natural intelligence\, thanks to new tools for better data collection and analysis from the brain; in the development of machine learning algorithms for solving real-world problems; and in the availability of scalable computing substrates that are smaller\, denser\, faster and feature parallel processing capabilities. \nIn this workshop\, we combine all the above towards a more efficient and powerful implementation of intelligent systems. Specifically\, our objective is to pinpoint what current ideas from machine learning and neuroscience can lead to practical designs for implementing low-power and miniaturized neuromorphic intelligent systems. To do so\, in a setting that fosters brainstorming and cross-fertilization\, we stimulate exchange of ideas on topics in which biology\, modeling\, and engineering are dealt with simultaneously. These topics will range from fundamental principles such as learning\, memory and the neurobiology of time; to high-level functions such as navigation\, embodiment and active sensing. \nThe mission of the CapoCaccia Workshops for Neuromorphic Intelligence is to understand the principles of biological intelligence and apply this knowledge in technologies\, for the good of all mankind. \nThe workshop features open and highly interactive discussion sessions in the morning; hands-on projects\, tutorials\, and hardware and software jamming sessions during the day; and free-form discussions in the evenings. \nThe workshop is open to everyone\, but since resources are limited\, we can accept only a limited number of registrations. Due to the limited number of hotel rooms\, Ph.D. students are expected to pair up and share rooms. All participants are encouraged to stay for the full two week period\, but can stay for less if necessary
URL:https://www.neuropac.info/event/capocaccia-workshop-2023/
LOCATION:Alghero\, Sardinia\, Italy\, Alghero\, Sardinia\, Italy
CATEGORIES:Workshop
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20230426T180000
DTEND;TZID=UTC:20230426T193000
DTSTAMP:20260416T150919
CREATED:20230127T223705Z
LAST-MODIFIED:20230127T223705Z
UID:10000009-1682532000-1682537400@www.neuropac.info
SUMMARY:Hands-on session with Xylo and Rockpool
DESCRIPTION:Speaker bio: Dylan Muir is the Vice President for Global Research Operations; Director for Algorithms and Applications; and Director for Global Business Development at SynSense. Dr. Muir is a specialist in architectures for neural computation. He has published extensively in computational and experimental neuroscience. At SynSense he is responsible for the company research vision\, and directing development of neural architectures for signal processing. Dr. Muir holds a Doctor of Science (PhD) from ETH Zurich\, and undergraduate degrees (Masters) in Electronic Engineering and in Computer Science from QUT\, Australia.
URL:https://www.neuropac.info/event/hands-on-session-with-xylo-and-rockpool/
LOCATION:Online
CATEGORIES:Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230425T080000
DTEND;TZID=America/Los_Angeles:20230425T090000
DTSTAMP:20260416T150919
CREATED:20230425T072512Z
LAST-MODIFIED:20230425T072512Z
UID:10000178-1682409600-1682413200@www.neuropac.info
SUMMARY:INRC Forum: James Knight
DESCRIPTION:Efficient training of sparse SNN classifiers using GeNN\nAbstract:Intuitive and easy to use application programming interfaces such as Keras have played a large part in the rapid acceleration of ANN-based machine learning. We want to unlock the potential of spike-based machine learning in the same way\, so here we present mlGeNN\, an easy way to define\, train and test spiking neural networks using GeNN — our efficient GPU-accelerated SNN simulator. Using GeNN\, we demonstrate that we can use e-prop to train recurrent SNN classifiers on datasets including the Spiking Heidelberg Digits (SHD) and DVS gesture. We show that these classifiers can not only offer comparable performance to LSTMs but are up to 7× faster when performing inference on the same GPU hardware. As GeNN is designed to exploit sparse connectivity\, by replacing the dense recurrent connectivity in classifier models with random sparse connectivity\, we can reduce the time taken to train such models by almost 10× — although this results in some reduction in classification accuracy. However\, in biological brains\, alongside the changes to the strength of existing synapses driven by synaptic plasticity\, structural plasticity prunes unused synapses and forms new ones. The Deep-R learning rule provides a framework for combining gradient-based learning with structural plasticity and by combining Deep-R with e-prop\, we demonstrate that the aforementioned reduction in classification accuracy can be eliminated\, even in very sparsely connected models. \nBio: Jamie Knight received his BEng degree in Electronic Engineering from the University of Warwick in 2006. After working as a games developer for several years\, he received an MPhil in Advanced Computer Science from the University of Cambridge in 2013 and a PhD in Computer Science from the University of Manchester in 2016. His doctoral work focussed on using the SpiNNaker neuromorphic supercomputer to simulate large-scale computational neuroscience models with synaptic plasticity. Since 2017 Jamie has worked at the University of Sussex\, first as a Research Fellow focussing on using GPU hardware to accelerate spiking neural network based robot controllers and\, since 2022\, as a EPSRC Research Software Engineering Fellow focussing on spike-based machine learning and the software to enable it. \nFor the meeting link\, see the full INRC Forum Spring 2023 Schedule (accessible only to INRC Affiliates and Fully Engaged Members).
URL:https://www.neuropac.info/event/inrc-forum-bruno-olshausen-2-4/
LOCATION:Online
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20230420T163000
DTEND;TZID=UTC:20230420T173000
DTSTAMP:20260416T150919
CREATED:20230127T222256Z
LAST-MODIFIED:20230828T170621Z
UID:10000041-1682008200-1682011800@www.neuropac.info
SUMMARY:Theory of Neuromorphic Computing
DESCRIPTION:Recurring discussion meeting by researchers interested in the theory of neuromorphic computing. \nHosted by Arne Diehl and Johan Kwisthout of Radboud University. To join the meetings\, please contact Arne Diehl: arne.diehl@donders.ru.nl.
URL:https://www.neuropac.info/event/theory-of-neuromorphic-computing/2023-04-20/
LOCATION:Online
CATEGORIES:Discussion
ORGANIZER;CN="Arne Diehl":MAILTO:arne.diehl@donders.ru.nl
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20230418T210000
DTEND;TZID=Europe/Amsterdam:20230418T223000
DTSTAMP:20260416T150919
CREATED:20230320T142706Z
LAST-MODIFIED:20230320T142706Z
UID:10000033-1681851600-1681857000@www.neuropac.info
SUMMARY:NeuroPAC Seminar: Forum on Neuromorphic Navigation
DESCRIPTION:Panelists: \n\nAndrew Davidson\, Imperial College\, London\nKostas Daniilidis\, University of Pennsylvania\nMichael Milford\, Queensland University of Technology\n\nJoin the seminar: https://umd.zoom.us/j/93344217202 \nMore information: https://www.neuropac.info/seminars/
URL:https://www.neuropac.info/event/neuropac-seminar-forum-on-neuromorphic-navigation/
LOCATION:Online
CATEGORIES:Symposium,Talk
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230418T080000
DTEND;TZID=America/Los_Angeles:20230418T090000
DTSTAMP:20260416T150919
CREATED:20230416T091939Z
LAST-MODIFIED:20230416T091939Z
UID:10000177-1681804800-1681808400@www.neuropac.info
SUMMARY:INRC Forum: Akshit Saradagi
DESCRIPTION:Neuromorphic sensing in sub-terranean environments and neuromorphic solvers for model predictive control\nAbstract: In this talk\, I will be presenting some recent results in Neuromorphic Engineering from the Robotics and AI group at Luleå University of Technology\, Sweden.\nIn the first half of my talk\, I will be presenting a novel LiDAR and event camera fusion framework for fast and precise object and human detection in subterranean (SubT) environments. The fusion framework caters to the wide variety of adverse lighting conditions found in SubT environments\, such as low or no light\, high-contrast zones and in the presence of blinding light sources. The proposed fusion uses intensity filtering and K-means clustering on the LiDAR point cloud and frequency filtering and connectivity clustering on the events induced in an event camera by the returning LiDAR beams. The fusion framework was experimentally validated in a real SubT environment (a mine) with a Pioneer 3AT mobile robot. The experimental results show real-time performance for human detection and the NMPC-based controller allows for reactive tracking of a human or object of interest\, even in complete darkness.\nIn the second half of the talk\, I will be presenting our preliminary results on using neuromorphic solvers for solving quadratic programs arising in Model Predictive Control (MPC). More specifically\, we employed the floating-point LAVA QP solver\, which emulates the Proportional-Integral Projected Gradient (PIPG) Method for solving QP problems\, to solve terminally constrained MPC problems. The objective function in linear MPC problems being strongly convex\, the LAVA QP solver ensures that the distance to optimum and the constraint violation converge to zero at the rate of O(1/k^2) and O(1/k^3) respectively\, with ‘k’ being the number of solver iterates. Given this peculiar convergence property of the solver\, I will present a sketch of our proof for asymptotic stability of the closed loop system\, along with the simulation-based validation. \nBio: Akshit Saradagi is a Postdoctoral researcher in the Robotics and AI group at Luleå University of Technology\, Sweden. He received his M.S and Ph.D dual degree from the Indian Institute of Technology Madras (IITM)\, Chennai\, India. His current research focusses on distributed control of multi-agent systems\, control barrier functions-based safety guarantees in Robotics\, applications of Neuromorphic Computing in Robotics and control under resource constraints. \nFor the meeting link\, see the full INRC Forum Spring 2023 Schedule (accessible only to INRC Affiliates and Fully Engaged Members).
URL:https://www.neuropac.info/event/inrc-forum-bruno-olshausen-2-3/
LOCATION:Online
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230411T080000
DTEND;TZID=America/Los_Angeles:20230411T090000
DTSTAMP:20260416T150919
CREATED:20230416T091845Z
LAST-MODIFIED:20230416T091845Z
UID:10000176-1681200000-1681203600@www.neuropac.info
SUMMARY:INRC Forum: Guido de Croon
DESCRIPTION:Neuromorphic sensing and processing for small\, autonomous drones\n\n\n\nAbstract: Small drones are promising for many applications\, such as search-and-rescue\, greenhouse monitoring\, or keeping track of stock in warehouses. Since they are small\, they can fly in narrow areas. Moreover\, their light weight makes them very safe for flight around humans. However\, making such small drones fly completely by themselves is an enormous challenge due to the extreme resource restrictions in terms of sensing and processing. In my talk\, I will discuss the promises of novel neuromorphic sensing and processing technologies for autonomous flight of small drones\, illustrating this with recent experiments from our lab. Specifically\, I will delve into our multi-year effort to create a fully neuromorphic vision-to-control pipeline\, going from raw events to low-level control commands. Recently\, we have achieved this feat for optical-flow-based ego-motion estimation and control\, implementing the spiking neural network on the Loihi Kapoho bay onboard of a free-flying drone. \n\n\n\nBio: Guido de Croon received his M.Sc. and Ph.D. in the field of Artificial Intelligence (AI) at Maastricht University\, the Netherlands. His research interest lies with computationally efficient\, bio-inspired algorithms for robot autonomy\, with an emphasis on computer vision. Since 2008 he has worked on algorithms for achieving autonomous flight with small and light-weight flying robots\, such as the DelFly flapping wing MAV. In 2011-2012\, he was a research fellow in the Advanced Concepts Team of the European Space Agency\, where he studied topics such as optical flow based control algorithms for extraterrestrial landing scenarios. After his return at TU Delft\, his work has included fully autonomous flight of a 20-gram DelFly\, a new theory on active distance perception with optical flow\, and a swarm of tiny drones able to explore unknown environments. Currently\, he is Full Professor at TU Delft and scientific lead of the Micro Air Vehicle lab (MAVLab) of Delft University of Technology. \nFor the meeting link\, see the full INRC Forum Spring 2023 Schedule (accessible only to INRC Affiliates and Fully Engaged Members).
URL:https://www.neuropac.info/event/inrc-forum-bruno-olshausen-2-2/
LOCATION:Online
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230411
DTEND;VALUE=DATE:20230415
DTSTAMP:20260416T150919
CREATED:20230114T164825Z
LAST-MODIFIED:20230114T164825Z
UID:10000001-1681171200-1681516799@www.neuropac.info
SUMMARY:NICE
DESCRIPTION:The 2023 Neuro-Inspired Computing Elements (NICE) Conference is the 10th annual meeting of researchers in the neural computing field. Like previous editions\, NICE 2023 will focus on the interplay between neural theory\, neural algorithms\, neuromorphic architectures and hardware\, and applications for neural computing technology. \nNICE aims to involve diverse participation from all over the world and bring together research communities with universities\, government\, and industry.
URL:https://www.neuropac.info/event/nice/
LOCATION:University of Texas at San Antonio\, San Antonio\, TX\, United States
CATEGORIES:Conference
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20230406T163000
DTEND;TZID=UTC:20230406T173000
DTSTAMP:20260416T150919
CREATED:20230127T222256Z
LAST-MODIFIED:20230828T170621Z
UID:10000040-1680798600-1680802200@www.neuropac.info
SUMMARY:Theory of Neuromorphic Computing
DESCRIPTION:Recurring discussion meeting by researchers interested in the theory of neuromorphic computing. \nHosted by Arne Diehl and Johan Kwisthout of Radboud University. To join the meetings\, please contact Arne Diehl: arne.diehl@donders.ru.nl.
URL:https://www.neuropac.info/event/theory-of-neuromorphic-computing/2023-04-06/
LOCATION:Online
CATEGORIES:Discussion
ORGANIZER;CN="Arne Diehl":MAILTO:arne.diehl@donders.ru.nl
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20230404T180000
DTEND;TZID=UTC:20230404T193000
DTSTAMP:20260416T150919
CREATED:20230127T223552Z
LAST-MODIFIED:20230127T223552Z
UID:10000008-1680631200-1680636600@www.neuropac.info
SUMMARY:Hands-on session with Sinabs and Speck
DESCRIPTION:Speaker bio: Gregor Lenz graduated with a Ph.D. in neuromorphic engineering from Sorbonne University. He thinks that technology can learn a thing or two from how biological systems process information. \nHis main interests are event cameras that are inspired by the human retina and spiking neural networks that mimic human brain in an effort to teach machines to compute a bit more like humans do. At the very least there are some power efficiency gains to be made\, but hopefully more! Also he loves to build open source software for spike-based machine learning. You can find more information on his personal website. \nHe is the maintainer of two open source projects in the field of neuromorphic computing\, Tonic and expelliarmus.
URL:https://www.neuropac.info/event/hands-on-session-with-sinabs-and-speck/
LOCATION:Online
CATEGORIES:Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230404T080000
DTEND;TZID=America/Los_Angeles:20230404T090000
DTSTAMP:20260416T150919
CREATED:20230331T122014Z
LAST-MODIFIED:20230331T122032Z
UID:10000175-1680595200-1680598800@www.neuropac.info
SUMMARY:INRC Forum: Arto Nurmikko
DESCRIPTION:Efficient Decoding of Multipoint Spiking Events Recorded by A Network of Wireless Biosensors\n\n\nAbstract: Our lab is developing tools for brain-machine interfaces using a concept of spatially distributed wireless microsensors\, “neurograins” implanted in a functional cortical area of interest (motor\, auditory\, visual). When a given sensor detects a spiking event\, the signal is immediately sent to an external radio-frequency receiver as a binary “1”. Thus\, for a network of thousand neurograins\, one goal of an ongoing research project\, the received data at the external detector is a stream of spikes in which the cortical computations of interest are embedded. Based on our work on smaller ensembles (hundred neurograins)\, we have discovered a major computational bottleneck in detecting and decoding signals for large ensembles of neurograins for a real-time (wearable/portable brain-interface systems. In this work\, we explore and apply the Loihi platform to integrate the demodulation (time-series correlation) and neural population decoding (spike-timing based model) steps into one parallel process. \nBio: Prof. Arto Nurmikko is a L. Herbert Ballou University Professor of Engineering and Physics at Brown. He recived his degrees from University of California\, Berkeley\, and did postdoctoral work at the Hebrew University (Jerusalem) and MIT. Prof. Nurmikko’s research spans the areas of neuroengineering\, photonics\, microelectronics\, nanosciences\, and the translation of device research to new technologies in physical and life science applications. Currently\, his research interests are focused on implantable neural interfaces. \nFor the meeting link\, see the full INRC Forum Spring 2023 Schedule (accessible only to INRC Affiliates and Fully Engaged Members).
URL:https://www.neuropac.info/event/inrc-forum-arto-nurmikko/
LOCATION:Online
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230328T080000
DTEND;TZID=America/Los_Angeles:20230328T090000
DTSTAMP:20260416T150919
CREATED:20230331T121912Z
LAST-MODIFIED:20230331T121924Z
UID:10000174-1679990400-1679994000@www.neuropac.info
SUMMARY:INRC Forum: Garrett Kenyon
DESCRIPTION:Sparse Coding with Locally Competitive Algorithm on Loihi 2\nBio: Garrett T. Kenyon received the BA degree in physics from the University of California at Santa Cruz in 1984 and the MS and PhD degrees in physics from the University of Washington in Seattle in 1986 and 1990\, respectively. He received further postdoctoral training at the Baylor College of Medicine\, Division of Neuroscience\, and at the University of Texas Medical School\, Houston\, Department of Neurobiology and Anatomy. He has been a staff member in the Biological and Quantum Physics group at the Los Alamos National Laboratory since 2001. His research interests involve the application of computer simulations and theoretical techniques to the analysis of computation in biological neural networks. \nFor the meeting link\, see the full INRC Forum Spring 2023 Schedule (accessible only to INRC Affiliates and Fully Engaged Members).
URL:https://www.neuropac.info/event/inrc-forum-garrett-kenyon/
LOCATION:Online
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230328
DTEND;VALUE=DATE:20230401
DTSTAMP:20260416T150919
CREATED:20230129T160341Z
LAST-MODIFIED:20230129T160341Z
UID:10000015-1679961600-1680307199@www.neuropac.info
SUMMARY:Human Brain Project Summit 2023
DESCRIPTION:The Human Brain Project Summit 2023 provides an open forum for hundreds of researchers\, plus policy makers\, media and public\, to discuss exciting scientific results\, the latest developments in the project\, and the cutting-edge services and tools available on the EBRAINS Research Infrastructure is a great opportunity to share the latest developments of the Human Brain Project with the community and external audiences. It is also meant to be a valuable moment of exchange\, discussion\, and feedback. \nClick here for more details.
URL:https://www.neuropac.info/event/human-brain-project-summit-2023/
LOCATION:Marseille\, France\, Marseille\, France
CATEGORIES:Conference,Workshop
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230327
DTEND;VALUE=DATE:20230330
DTSTAMP:20260416T150919
CREATED:20230129T162712Z
LAST-MODIFIED:20230129T162712Z
UID:10000016-1679875200-1680134399@www.neuropac.info
SUMMARY:tinyML Summit 2023
DESCRIPTION:The tinyML Summit 2023 will be the premier gathering of key tinyML members from all aspects of the ecosystem. This year\, end-users\, innovators\, and business leaders will be invited to encompass the expanding breadth of industries impacted by the maturing tinyML technology and application space. The tinyML Summit 2023 will provide a unique environment to have focused\, high-impact presentations and conversations from both suppliers and users to advance the accessibility and adoption of tinyML solutions. No matter where you are in the Edge Computing AI/ML supply chain\, this is the must-attend event for 2023. \nThe tinyML Research Symposium 2023 will be held in conjunction with the tinyML Summit.  The Research Symposium is the premier annual gathering of senior level technical experts and decision makers representing fast growing global tinyML community.
URL:https://www.neuropac.info/event/tinyml-summit-2023/
LOCATION:Hyatt Regency\, San Francisco\, CA\, United States
CATEGORIES:Conference,Workshop
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20230323T163000
DTEND;TZID=UTC:20230323T173000
DTSTAMP:20260416T150919
CREATED:20230127T222256Z
LAST-MODIFIED:20230828T170621Z
UID:10000039-1679589000-1679592600@www.neuropac.info
SUMMARY:Theory of Neuromorphic Computing
DESCRIPTION:Recurring discussion meeting by researchers interested in the theory of neuromorphic computing. \nHosted by Arne Diehl and Johan Kwisthout of Radboud University. To join the meetings\, please contact Arne Diehl: arne.diehl@donders.ru.nl.
URL:https://www.neuropac.info/event/theory-of-neuromorphic-computing/2023-03-23/
LOCATION:Online
CATEGORIES:Discussion
ORGANIZER;CN="Arne Diehl":MAILTO:arne.diehl@donders.ru.nl
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230321T180000
DTEND;TZID=Europe/Berlin:20230321T193000
DTSTAMP:20260416T150919
CREATED:20230114T170109Z
LAST-MODIFIED:20230114T170109Z
UID:10000003-1679421600-1679427000@www.neuropac.info
SUMMARY:Evolutionary Optimization for Neuromorphic Systems
DESCRIPTION:Speaker bio: Catherine (Katie) Schuman is an Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of Tennessee (UT). She received her Ph.D. in Computer Science from UT in 2015\, where she completed her dissertation on the use of evolutionary algorithms to train spiking neural networks for neuromorphic systems. Katie previously served as a research scientist at Oak Ridge National Laboratory\, where her research focused on algorithms and applications of neuromorphic systems. Katie co-leads the TENNLab Neuromorphic Computing Research Group at UT. She has over 100 publications as well as seven patents in the field of neuromorphic computing. She received the Department of Energy Early Career Award in 2019.
URL:https://www.neuropac.info/event/evolutionary-optimization-for-neuromorphic-systems/
LOCATION:Online
CATEGORIES:Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230321T080000
DTEND;TZID=America/Los_Angeles:20230321T090000
DTSTAMP:20260416T150919
CREATED:20230331T121734Z
LAST-MODIFIED:20230331T121734Z
UID:10000173-1679385600-1679389200@www.neuropac.info
SUMMARY:INRC Event: Neuromorphic Dynamic Noise Suppression (N-DNS) Challenge
DESCRIPTION:The Intel Neuromorphic DNS Challenge is a unique opportunity to advance state-of-the-art neuromorphic algorithms research and win up to $55\,000 of prize money.\nYou need not be an INRC member to participate in this challenge\, however you will need to join in order to develop solutions for Track 2\, see below. Kick-off presentation and recording from the March 21\, 2023 INRC Forum session is available via this link.
URL:https://www.neuropac.info/event/inrc-forum-bruno-olshausen-3/
LOCATION:Online
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230315
DTEND;VALUE=DATE:20230316
DTSTAMP:20260416T150919
CREATED:20230225T210608Z
LAST-MODIFIED:20230311T160753Z
UID:10000027-1678838400-1678924799@www.neuropac.info
SUMMARY:Abstract Deadline: International Conference on Neuromorphic\, Natural and Physical Computing
DESCRIPTION:We are happy to announce the “Neuromorphic\, Natural and Physical Computing: Interdisciplinary Foundations (NNPC 2023)”\, organized with generous support by the Volkswagen Foundation. The conference will take place the 25th – 27th of October 2023 in Hanover\, Germany\, and the deadline for submitting a 2-page abstract is March 15th. \nThe general aim of NNPC 2023 is to boost interdisciplinary transfer of ideas and networking in the wider fields of non-digital computing. NNPC 2023 is a successor to the 2018 conference “Cognitive Computing: Merging Concepts with Hardware” (https://nnpc-conference.com/2018) whose very productive and motivating format will be kept\, as well as the location and the generous funding conditions. \nEach session is devoted to a specific theme. We encourage active engagement of attendants by requiring submission of a 2-page abstract on a subject relating to one of the session themes. These abstracts are peer-reviewed. From the accepted abstracts three are chosen for oral presentations and the remaining ones for posters. Importantly\, novelty is not essential as our aim is to make knowledge to diffuse across boundaries of the scientific domains involved.
URL:https://www.neuropac.info/event/abstract-deadline-international-conference-on-neuromorphic-natural-and-physical-computing/
LOCATION:Online
CATEGORIES:Conference,Deadline
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230314T080000
DTEND;TZID=America/Los_Angeles:20230314T090000
DTSTAMP:20260416T150919
CREATED:20230331T121426Z
LAST-MODIFIED:20230331T121701Z
UID:10000172-1678780800-1678784400@www.neuropac.info
SUMMARY:INRC Forum: Thomas Nowotny
DESCRIPTION:Loss shaping enhances exact gradient learning with EventProp in Spiking Neural Networks\nAbstract: In a recent paper Wunderlich and Pehle (2021) introduced the EventProp algorithm that enables training spiking neural networks by gradient descent on exact gradients. In this talk I will present extensions of EventProp to support a wider class of loss functions and an implementation in the GPU enhanced neuronal networks framework (GeNN) which exploits sparsity. The GPU acceleration allows us to test EventProp extensively on more challenging learning benchmarks. We find that EventProp performs well on some tasks but for others there are issues where learning is slow or fails entirely. We have discovered that the problems relate to the exact gradient of the loss function not providing information about loss changes due to spike creation or spike deletion. Depending on the details of the task and loss function\, descending the exact gradient with EventProp can lead to the deletion of important spikes and so to an inadvertent increase of the loss and decrease of classification accuracy and hence a failure to learn. In other situations\, the lack of knowledge about the benefits of creating additional spikes can lead to a lack of gradient flow into earlier layers\, slowing down learning. We are trying to overcome these problems in the form of `loss shaping’\, where we introduce a suitable weighting function into an integral loss to increase gradient flow from the output layer towards earlier layers. I will show example result for the Spiking Heidelberg Digits and sequential spiking MNIST where we achieve (close to) state-of-the-art performance. \nBio. Prof. Thomas Nowotny has a background in theoretical physics. After his PhD from Leipzig University in 2001 he started working in Computational Neuroscience and bio-inspired AI at the Institute for non-linear Science at UCSD. He is now a Professor in Informatics at the University of Sussex and the head of the AI research group. His interests include olfaction\, hybrid systems\, spiking neural networks and their efficient simulation\, bio-inspired AI and algorithms for neuromorphic computing. \nFor the meeting link\, see the full INRC Forum Spring 2023 Schedule (accessible only to INRC Affiliates and Fully Engaged Members).
URL:https://www.neuropac.info/event/inrc-forum-thomas-nowotny-2/
LOCATION:Online
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230309
DTEND;VALUE=DATE:20230315
DTSTAMP:20260416T150919
CREATED:20230129T223003Z
LAST-MODIFIED:20230129T223003Z
UID:10000026-1678320000-1678838399@www.neuropac.info
SUMMARY:Computational and Systems Neuroscience (COSYNE) 2023
DESCRIPTION:The annual COSYNE conference provides an inclusive forum for the exchange of experimental and theoretical approaches to problems in systems neuroscience\, in order to understand how neural systems are built and function.
URL:https://www.neuropac.info/event/computational-and-systems-neuroscience-cosyne-2023/
LOCATION:Montreal\, Montreal\, Canada
CATEGORIES:Conference
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230307T080000
DTEND;TZID=America/Los_Angeles:20230307T090000
DTSTAMP:20260416T150919
CREATED:20230331T120956Z
LAST-MODIFIED:20230331T121020Z
UID:10000171-1678176000-1678179600@www.neuropac.info
SUMMARY:INRC Forum: Bruno Olshausen
DESCRIPTION:Computing with Dynamics\nAbstract: Is the brain a computer?  Or is it a dynamical system?  While computation serves as a useful metaphor for cognitive processes\, as we delve into the neuroanatomical circuits and physiological properties of brains we encounter structures and phenomena that seem foreign and unfamiliar in terms of standard computing models.  Highly recurrent circuits with massive interconnectivity\, attractor dynamics\, oscillations\, traveling waves\, and active sensing are all hallmarks of biological neural systems.  How do we make sense of these things in terms of “computation?”  Or are we working with the wrong metaphor?  Here I shall present a number of recent findings from neuroscience that challenge us to think in new ways about the underlying physical processes governing perception and cognition. \nBio: Bruno OIshausen is Professor of Neuroscience and Optometry at the University of California\, Berkeley.  He also serves as Director of the Redwood Center for Theoretical Neuroscience\, an interdisciplinary research group focusing on mathematical and computational models of brain function.  He received B.S. and M.S. degrees in Electrical Engineering from Stanford University\, and a Ph.D. in Computation and Neural Systems from the California Institute of Technology.  Prior to Berkeley he was a member of the Departments of Psychology and Neurobiology\, Physiology & Behavior at UC Davis.  During postdoctoral work with David Field at Cornell he developed the sparse coding model of visual cortex which provides a linking principle between natural scene statistics and the response properties of visual neurons.  Olshausen’s current research aims to understand the information processing strategies employed by the brain for doing tasks such as object recognition and scene analysis.  This work seeks not only to advance our understanding of the brain\, but also to discover new algorithms for scene analysis based on how brains work. \nFor the meeting link\, see the full INRC Forum Spring 2023 Schedule (accessible only to INRC Affiliates and Fully Engaged Members).
URL:https://www.neuropac.info/event/inrc-forum-bruno-olshausen/2023-03-07/
LOCATION:Online
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20230302T180000
DTEND;TZID=UTC:20230302T193000
DTSTAMP:20260416T150919
CREATED:20230127T223200Z
LAST-MODIFIED:20230127T223200Z
UID:10000007-1677780000-1677785400@www.neuropac.info
SUMMARY:Hands-on session with snnTorch
DESCRIPTION:Bio: Jason K. Eshraghian is an Assistant Professor at the Department of Electrical and Computer Engineering at UC Santa Cruz\, CA\, USA. Prior to that\, he was a Post-Doctoral Researcher at the Department of Electrical Engineering and Computer Science\, University of Michigan in Ann Arbor. He received the Bachelor of Engineering (Electrical and Electronic) and the Bachelor of Laws degrees from The University of Western Australia\, WA\, Australia in 2016\, where he also completed his Ph.D. Degree. \nProfessor Eshraghian was awarded the 2019 IEEE VLSI Best Paper Award\, the Best Paper Award at 2019 IEEE Artificial Intelligence CAS Conference\, and the Best Live Demonstration Award at 2020 IEEE ICECS for his work on neuromorphic vision and in-memory computing using RRAM. He currently serves as the secretary-elect of the IEEE Neural Systems and Applications Committee\, and was a recipient of the Fulbright Future Fellowship (Australian-America Fulbright Commission)\, the Forrest Research Fellowship (Forrest Research Foundation)\, and the Endeavour Fellowship (Australian Government).
URL:https://www.neuropac.info/event/hands-on-session-with-snntorch-2/
LOCATION:Online
CATEGORIES:Tutorial
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20230228T100000
DTEND;TZID=UTC:20230228T113000
DTSTAMP:20260416T150919
CREATED:20230129T155909Z
LAST-MODIFIED:20230129T155909Z
UID:10000013-1677578400-1677583800@www.neuropac.info
SUMMARY:EBRAINS - a solution-driven approach to enable brain science and technologies
DESCRIPTION:There will be great opportunities for data scientists looking to expand their knowledge\, companies looking for project partnerships\, cognitive psychologists who need the inspiration to improve their technology and more. \nProgramme: \n\n10h00 – 10h05: Introduction by France Nivelle\n10h05 – 10h20: EBRAINS Introduction and Scientific vision by Prof. dr. Viktor Jirsa\, Chief Science Officer at EBRAINS\, Professor at Aix-Marseille Université\, INS Director / DR CNRS\n10h20 – 10h35: EBRAINS Neurotechnology approach by Prof. Dr. Pieter Roelfsema\, MD\, PhD\, Director of the Netherlands Institute for Neuroscience\n10h35 – 10h50: The future of Brain Health within the EBRAINS Research Infrastructure by Univ.-Prof. Dr. med. Petra Ritter\, BIH Johanna Quandt Professor for Brain Simulation\, Director Brain Simulation Section\, Berlin Institute of Health & Dept. of Neurology\, Charité University Hospital Berlin\n10h50 – 11h05: A solution approach for EBRAINS Research Infrastructureby Prof. dr. ir. Liesbet Peeters\, Professor at the Biomedical Research Institute and Data Science Institute of Hasselt University\, Multiple Sclerosis Data Alliance Core Partner\n11h05 – 11h10: Concluding remarks by France Nivelle\n11h10 – 11h30: Q&A session\n\nClick here to register.
URL:https://www.neuropac.info/event/ebrains-a-solution-driven-approach-to-enable-brain-science-and-technologies/
LOCATION:Online
CATEGORIES:Symposium
END:VEVENT
END:VCALENDAR