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Added Workshop on Model Inversion
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---
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authors:
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- Andrea Brovelli
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date: 2025-06-12
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publishDate: 2025-05-13
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draft: false
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image:
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focal_point: Center
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placement: 2
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preview_only: true
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projects: []
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tags:
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- events
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title: '2025-06-26 : Workshop on Model Inversion'
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subtitle: '"Joint INT-INS workshop on model inversion techniques for neuroscience: linking neural models to brain data"'
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summary: '"Joint INT-INS workshop on model inversion techniques for neuroscience: linking neural models to brain data".'
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---
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* When: June 12th ***14:00 to 18:00***
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* Where: Salle Laurent Vinay, _Institut de Neurosciences de la Timone_, Marseille, France.
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> Have you ever asked yourself how to find the neural model that best describes your data? What a good question! For complex models, no easy solution exists. Generally, this issue is referred to as "model inversion", and it often represents an ill-posed problem in data science, where no unique solution is at hand. However, recent advances in ML and AI are providing interesting tools that can be used to perform model inversion and fit neural models to brain data.
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The aim of the workshop is to provide an overview of projects at INT and INS focusing on model inversion. Although technical, the workshop will try to provide an overview for experimentalists and those who are not familiar with model inversion techniques.
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PROGRAM
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14:00 Nina Baldy (TNG-INS) - Dynamic Causal Modeling in Probabilistic Programming Languages
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14:45 Pedro Garcia (BraiNets-INT) - A dynamic causal model to infer effective connectivity from meg induced responses (high-gamma-activity): a workflow for model bayesian inversion
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15:30 Pause :coffee: :mate_drink:
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15:45 Jean-Didier Lemaréchal (BraiNets-INT) - Bayesian inference applied to neuronal models: methods & applications
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16:30 Cyprien Dautrevaux (BraiNets-INT) - TBA
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17:15 Abolfazl Ziaeemehr (TNG-INS) - Virtual Brain Inference (VBI): A flexible and integrative toolkit for efficient probabilistic inference on virtual brain models
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18:00 Glam Rock :beers: :peanut
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{{% callout note %}}
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TBA
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{{% /callout %}}

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