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Keynote
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Agnes Korcsak-Gorzo
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Biologically plausible supervised learning in large-scale networks
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Fynn Dobler, Maxime Carrire
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Lost in translation: How porting a brain-constrained model of word semantics to NEST revealed undocumented model assumptions
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Pablo Martinez-Canada
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From Circuits to Signals and Back: Integrating Biophysical Forward Modelling and Simulation-Based Inference to Decode Brain Dynamics
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Tutorial
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Agnes Korcsak-Gorzo
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Biologically plausible supervised learning with event-driven eligibility propagation
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Charl Linssen, Pooja Babu
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Modeling and simulating neuron models from NESTML on neuromorphic hardware
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Willem Wybo
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Creating, analyzing, simplifying, and simulating biophysical neurons with NEAT
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Talks
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Carlos Enrique Gutierrez
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Neuro-Workflow: Agent-Assisted Brain Modeling
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Catherine Schofmann
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Scaling Neural Networks On Accelerators With Procedural Connectivity Generation
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Gianmarco Tiddia
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Scalable network construction method for NEST GPU enables efficient multi-GPU simulations
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Jan Eirik Skaar, Hans Ekkehard Plesser
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Practice report: Porting a complex network model from BRIAN2 to NEST
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Jan Vogelsang, Susanne Kunkel
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Rethinking Synapse Placement in NEST for Cache-Efficiency on Many-Core Exascale Architectures
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Mahesh Madhav, Hans Ekkehard Plesser
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Issue #3217: Making NEST a part of the SPEC CPU 2026 benchmark suite
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Melissa Lober
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NUMA balancing hampering performance of spiking network simulations
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Pedro Ribeiro Pinheiro
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Simulating prefrontal cortex dynamics in a data-driven spiking neural network
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Rafael Fernando Gigante
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A Large-Scale Spiking Network Model of the Primary Motor Cortex
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Razvan Gamanut
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Subthreshold Dynamics in a Gap-Junction-Coupled PV Network Model of the Claustrum
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Sinovia Fotiadou
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Bridging NEST Microcircuits to Zerlaut Mean-Field Models: A Reproducible Single-Region Workflow for the Virtual Brain Twin
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Tibor Rozsa
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Toward reliable visual prosthetic stimulation under highly variable spontaneous activity
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Poster
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Alex Dimitrov et al
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Statistics of spiking neural networks based on counting processes
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Ariel Shmilli et al
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Long-term memory consolidation in spiking neural networks
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Camilo Jara Do Nascimento et al
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Dendritic plateau potentials enable learning over long timescales
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Charl Linssen et al
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Automated code generation of advanced plasticity rules for the SpiNNaker neuromorphic platform using NESTML
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Daniel Todt
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Parameter specification in spiking neural networks using NEST and simulation-based inference
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José Villamar et al
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Scaling up to billions of spiking neurons and trillions of synapses with NEST GPU
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Krishna Kant Singh
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Empowering Neuroscience Research with Portable HPC Containers
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Marie Olli
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Structural plasticity in large-scale spiking neural networks
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Markus Diesmann
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On polynomials in spiking neuronal network simulations
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Noah Ostendorf
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Motiforge: Flexible Motif-Constrained Network Generation for Structured Neural Architectures
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Pooja Babu
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Modeling and simulating two-compartment neuron model with NESTML on NEST GPU
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