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DTSTART;TZID=Europe/Zurich:20240205T180000
DTEND;TZID=Europe/Zurich:20240205T200000
DTSTAMP:20260417T170215
CREATED:20240105T080554Z
LAST-MODIFIED:20240105T080554Z
UID:10000274-1707156000-1707163200@www.neuropac.info
SUMMARY:Jens E. Pedersen @ ONM - NIR: A Unified Instruction Set for Brain-Inspired Computing
DESCRIPTION:Have you wondered how to use neuromorphic hardware platforms? \nAre you depressed by your power bill after you bought your >400W GPU rig? \nThen you came to the right place! \nIn this workshop\, we will show you how to move models from your favourite framework directly to neuromorphic hardware with 1-2 lines of code! We will present the technology behind\, the Neuromorphic Intermediate Representation \, and demonstrate how we can use it to run a live spiking convnet on the Speck chip. \nNIR is currently supported by Intel Loihi \, Speck \, SpiNNaker2 \, Xylo and a host of simulators\, including Norse \, snnTorch \, and Spyx . \nJoin us on the 5th of February to get your own hands-on experience with NIR and neuromorphic hardware! \nAll it requires is a computer and a bit of Python knowledge. \nAgenda: \n\n18:00 – 19:00: NIR introduction\n\nMotivation: coupling neuromorphic hardware and software\nDemonstrating NIR: from PyTorch to Speck\nQ&A\n\n\n19:00 – 20:00: Workshop\n\nHands-on experience with NIR via Jupyter Notebooks or custom models\nQ&A and collaborative discussions\n\n\n\nSpeakers: \n\nJens E. Pedersen \, PhD at the Neurocomputing Systems lab at KTH Royal Institute of Technology\, Sweden\n\nNote: The event will be hosted virtually. Stay tuned for the video link and further updates. \n\n\n\n\n\nAbout the Speaker\nJens is a computer scientist studying his PhD in neuromorphic computing at the KTH Royal Institute of Technology. Jens co-authored the Norse simulator and the AEStream event-based streaming library.
URL:https://www.neuropac.info/event/jens-e-pedersen-onm-nir-a-unified-instruction-set-for-brain-inspired-computing/
LOCATION:Online
CATEGORIES:Talk,Workshop
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20240207T160000
DTEND;TZID=Europe/Amsterdam:20240207T170000
DTSTAMP:20260417T170215
CREATED:20240130T002332Z
LAST-MODIFIED:20240130T002332Z
UID:10000278-1707321600-1707325200@www.neuropac.info
SUMMARY:Mahyar Shahsavari @ ELLIS MeetUp Nijmegen: Revolutionizing Intelligence
DESCRIPTION:Title:\n“Revolutionizing Intelligence: Bridging Minds and Machines with Neuromorphic Computing” \nAbstract\nNeuromorphic event-driven systems emulate the computational mechanisms of the brain through the utilization of spiking neural networks (SNN). Neuromorphic systems serve two primary application domains: simulating neural information processing in neuroscience and acting as accelerators for cognitive computing in engineering applications.\nIn this seminar\, we delve into the core principles of neuromorphic paradigm. Mahyar will discuss how this innovative approach addresses the limitations of traditional AI models in computation\, ushering in a new era of efficiency\, adaptability\, and parallel processing.\nThe presentation highlights key advancements\, such as spiking neural networks and neuromorphic hardware\, demonstrating their pivotal role in achieving brain-like computation and real-time processing. In this seminar the potential applications in industry\, robotics\, edge computing and beyond will be discussed\, ultimately inviting the audience to envision a harmonious integration of minds and machines through the revolutionary lens of neuromorphic computing. \nMicrosoft Teams Seminar Link
URL:https://www.neuropac.info/event/mahyar-shahsavari-ellis-meetup-nijmegen-revolutionizing-intelligence/
LOCATION:Nijmegen\, Nijmegen\, Netherlands
CATEGORIES:Talk,Workshop
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20240220
DTEND;VALUE=DATE:20240228
DTSTAMP:20260417T170215
CREATED:20231103T151303Z
LAST-MODIFIED:20231103T151303Z
UID:10000261-1708387200-1709078399@www.neuropac.info
SUMMARY:AAAI 2024
DESCRIPTION:38th Annual AAAI Conference on Artificial Intelligence\nThe purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers\, practitioners\, scientists\, students\, and engineers across the entirety of AI and its affiliated disciplines. AAAI-24 will feature technical paper presentations\, special tracks\, invited speakers\, workshops\, tutorials\, poster sessions\, senior member presentations\, competitions\, and exhibit programs\, and a range of other activities to be announced. \nWe expect for AAAI-24 to be an in-person conference – one author of all accepted papers will be expected to present work in person unless there are exceptional circumstances that prevent this. \n\n \n\n\n\n\n\n\nDriven by its disciplinary diversity\, AAAI has incubated numerous AI sub-disciplines and conferences and has nurtured for decades the cohesion of AI. New communities often emerge when two or more disciplines come together in order to explore new opportunities and perspectives; today\, both are plentiful. The purpose of this year’s Bridge Program is to tap into new sources of innovation by cultivating collaboration between two or more communities directed towards a common goal. Our interpretation of bridges is broad and encompasses disciplines within and outside of AI. Hence\, the communities that our Bridge Program is intended to bring together could be distinct subfields of AI\, such as planning and learning\, or different disciplines that contribute to and benefit from AI\, such as AI and the humanities.
URL:https://www.neuropac.info/event/aaai-2024/
LOCATION:Vancouver\, Canada\, Vancouver\, Canada
CATEGORIES:Conference
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240221
DTEND;VALUE=DATE:20240224
DTSTAMP:20260417T170215
CREATED:20231103T145110Z
LAST-MODIFIED:20231103T145110Z
UID:10000257-1708473600-1708732799@www.neuropac.info
SUMMARY:Neuronics 2024
DESCRIPTION:Neuronics Conference 2024\nBrain-inspired neuromorphic computing has emerged as a promising solution to overcome the computation bottlenecks in artificial intelligence (AI) applications. However\, traditional CMOS technologies\, which heavily relied on silicon\, face significant challenges such as volatility and energy inefficiency. These obstacles have hindered the rapid progress in the field. Thankfully\, recent developments in novel memory and memristive technologies\, have revitalized the pursuit of efficient and high-performance neuromorphic computing systems. \nThis conference aims to present the current status and cutting-edge advancements in the development of neuromorphic devices that emulate biological neural processes through device physics. A particular focus will be placed on memristive technologies as a promising devices for implementing various neuromorphic functions\, including artificial synapses\, neurons\, and dendrites. The different material platforms include conjugated polymers\, hydrogels\, nonmetal oxides\, correlated oxides\, transition metal oxides (TMOs)\, chalcogenides\, carbon-based materials\, phase change\, ferroelectric materials\, piezoelectric materials\,magnetics materials\, fluidics\, and nanocomposites. \nThe conference will also highlight the emerging fields of bioinspired ionotronics and mixed ionic-electronic-photonic materials. These areas focus on leveraging ionic motion and arrangement to control electronic properties and functions\, enabling the development of various functional devices. Topics of discussion will include electrolyte gating as an alternative to chemical doping\, organic and halide perovskites transistors\, various types of memristors\, ionic channels\, and their implications in the advancement of neuromorphic computing. \nResearchers will showcase circuits demonstrating full neuromorphic functionality\, such as unsupervised learning\, pattern recognition in neural networks\, and the neuroscientific aspects of artificial intelligence. Moreover\, the conference will explore the advancements in programmed/directed self-assembly and stimuli-responsive systems\, as well as their applications in smart sensing systems. These systems encompass a wide range of applications\, including optical sensing\, temperature sensing\, gas sensing\, strain sensing\, and more. The conference will also delve into haptic systems\, biosensors\, and image sensors\, exploring their integration with neuromorphic computing paradigms. \nThe conference will address the listed topics in an holistic view and joining together an interdisciplinary community from different research fields\, such as electronic\, materials science\, nanotechnology\, engineering\, computer science\, neurobiology\, computational neuroscience\, neural and biomedical-engineering. \nJoin us at this conference to engage in insightful discussions\, share knowledge\, and explore the exciting possibilities that brain-inspired neuromorphic computing and device physics offer for the future of artificial intelligence and computing systems.
URL:https://www.neuropac.info/event/neuronics-2024/
LOCATION:Valencia\, Valencia\, Spain
CATEGORIES:Conference
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Zurich:20240227T180000
DTEND;TZID=Europe/Zurich:20240227T193000
DTSTAMP:20260417T170215
CREATED:20240105T080743Z
LAST-MODIFIED:20240308T111522Z
UID:10000275-1709056800-1709062200@www.neuropac.info
SUMMARY:Aaron Spieler @ ONM - The ELM Neuron: An Efficient and Expressive Cortical Neuron Model Can Solve Long-Horizon Tasks
DESCRIPTION:From the Open Neuromorphic website. \nBiological cortical neurons are remarkably sophisticated computational devices\, temporally integrating their vast synaptic input over an intricate dendritic tree\, subject to complex\, nonlinearly interacting internal biological processes. \nWith the aim to explore the computational implications of leaky memory units and nonlinear dendritic processing\, we introduce the Expressive Leaky Memory (ELM) neuron model\, a biologically inspired phenomenological model of a cortical neuron. Remarkably\, by exploiting a few such slowly decaying memory-like hidden states and two-layered nonlinear integration of synaptic input\, our ELM neuron can accurately match the aforementioned input-output relationship with under ten-thousand trainable parameters. \nWe evaluate the model on various tasks with demanding temporal structures\, including the Long Range Arena (LRA) datasets\, as well as a novel neuromorphic dataset based on the Spiking Heidelberg Digits dataset (SHD-Adding). The ELM neuron reliably outperforms the classic Transformer or Chrono-LSTM architectures on these tasks\, even solving the Pathfinder-X task with over 70% accuracy (16k context length). \n\n\n\n\n\nAbout the Speaker\nAaron Spieler is a computational neuroscientist passionate about exploring the intersection of deep learning and neuroscience. After earning his Bachelor’s in Computer Science from the University of Potsdam\, he undertook an extended internship at Amazon Web Services working in deep learning based forecasting\, before further specializing with a Master’s in Computational Neuroscience at the University of Tübingen. Throughout his Master’s thesis and a subsequent internship at the Max Planck Institute for Intelligent Systems\, Aaron focused on phenomenological neuron modeling with applications to long-range prediction tasks. Pursuing this work allowed him to collaborate with excellent researchers from diverse backgrounds\, including Prof. Bernhard Schölkopf and Prof. Anna Levina.
URL:https://www.neuropac.info/event/aaron-spieler-onm-the-elm-neuron-an-efficient-and-expressive-cortical-neuron-model-can-solve-long-horizon-tasks/
LOCATION:Online
CATEGORIES:Talk,Workshop
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