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1000 results for “sanjay_ankur”
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A new version of the Open Source Brain (#OpenSourceBrain) model validation framework was just released. Please update your installations:
```
pip install -U OSBModelValidation
```https://github.com/OpenSourceBrain/osb-model-validation/releases/tag/v0.3.9
#OMV is a #Python package that allows you to validate your #NeuroML models against different simulation engines---to ensure that you get the same behaviours on all these engines. Examples:
https://github.com/OpenSourceBrain/.github/blob/main/testsheet/README.md
#FAIR #ComputationalNeuroscience #Neuroscience #ModelValidation
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A new release of PyNeuroML is available, please update your installations:
https://github.com/NeuroML/pyNeuroML/releases
```
pip install --upgrade pyneuroml
```#NeuroML #ComputationalNeuroscience #Neuroscience #Python #AcademicChatter
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A new release of PyNeuroML is available, please update your installations:
https://github.com/NeuroML/pyNeuroML/releases
```
pip install --upgrade pyneuroml
```#NeuroML #ComputationalNeuroscience #Neuroscience #Python #AcademicChatter
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A new release of PyNeuroML is available, please update your installations:
https://github.com/NeuroML/pyNeuroML/releases
```
pip install --upgrade pyneuroml
```#NeuroML #ComputationalNeuroscience #Neuroscience #Python #AcademicChatter
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A new release of PyNeuroML is available, please update your installations:
https://github.com/NeuroML/pyNeuroML/releases
```
pip install --upgrade pyneuroml
```#NeuroML #ComputationalNeuroscience #Neuroscience #Python #AcademicChatter
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In the next version, 0.6.6, all component classes in the #libNeuroML #Python API gain a quick method to list the parameters of their model objects. So, if you load a #NeuroML file/model, you can easily print the parameters of the different model entities. See the test in the pull request for a quick example:
https://github.com/NeuralEnsemble/libNeuroML/pull/208/files
#ComputationalNeuroscience #AcademicChatter #Neuroscience #FAIR
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In the next version, 0.6.6, all component classes in the #libNeuroML #Python API gain a quick method to list the parameters of their model objects. So, if you load a #NeuroML file/model, you can easily print the parameters of the different model entities. See the test in the pull request for a quick example:
https://github.com/NeuralEnsemble/libNeuroML/pull/208/files
#ComputationalNeuroscience #AcademicChatter #Neuroscience #FAIR
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In the next version, 0.6.6, all component classes in the #libNeuroML #Python API gain a quick method to list the parameters of their model objects. So, if you load a #NeuroML file/model, you can easily print the parameters of the different model entities. See the test in the pull request for a quick example:
https://github.com/NeuralEnsemble/libNeuroML/pull/208/files
#ComputationalNeuroscience #AcademicChatter #Neuroscience #FAIR
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#NeuroML is participating in #GSoC2025 again this year under @INCF . We're looking for people with some experience of #ComputationalNeuroscience to work on developing #standardised biophysically detailed computational models using #NeuroML #PyNN and #OpenSourceBrain.
Please spread the word, especially to students interested in modelling. We will help them learn the NeuroML ecosystem so they can use its standardised pipeline in their work.
https://docs.neuroml.org/NeuroMLOrg/OutreachTraining.html#google-summer-of-code
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#NeuroML is participating in #GSoC2025 again this year under @INCF . We're looking for people with some experience of #ComputationalNeuroscience to work on developing #standardised biophysically detailed computational models using #NeuroML #PyNN and #OpenSourceBrain.
Please spread the word, especially to students interested in modelling. We will help them learn the NeuroML ecosystem so they can use its standardised pipeline in their work.
https://docs.neuroml.org/NeuroMLOrg/OutreachTraining.html#google-summer-of-code
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#NeuroML is participating in #GSoC2025 again this year under @INCF . We're looking for people with some experience of #ComputationalNeuroscience to work on developing #standardised biophysically detailed computational models using #NeuroML #PyNN and #OpenSourceBrain.
Please spread the word, especially to students interested in modelling. We will help them learn the NeuroML ecosystem so they can use its standardised pipeline in their work.
https://docs.neuroml.org/NeuroMLOrg/OutreachTraining.html#google-summer-of-code
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#NeuroML is participating in #GSoC2025 again this year under @INCF . We're looking for people with some experience of #ComputationalNeuroscience to work on developing #standardised biophysically detailed computational models using #NeuroML #PyNN and #OpenSourceBrain.
Please spread the word, especially to students interested in modelling. We will help them learn the NeuroML ecosystem so they can use its standardised pipeline in their work.
https://docs.neuroml.org/NeuroMLOrg/OutreachTraining.html#google-summer-of-code
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Please see the paper for more details, and whether you’d like to use #NeuroML in your work, or support NeuroML in your tools/modelling pipelines, please come speak to us on any of our communication channels. Full documentation on NeuroML is here at https://docs.neuroml.org 9/9
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Please see the paper for more details, and whether you’d like to use #NeuroML in your work, or support NeuroML in your tools/modelling pipelines, please come speak to us on any of our communication channels. Full documentation on NeuroML is here at https://docs.neuroml.org 9/9
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Please see the paper for more details, and whether you’d like to use #NeuroML in your work, or support NeuroML in your tools/modelling pipelines, please come speak to us on any of our communication channels. Full documentation on NeuroML is here at https://docs.neuroml.org 9/9
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#NeuroML is a global community initiative. It is developed by an elected Editorial Board and overseen by a Scientific Committee. All the software/documentation/models produced in NeuroML are completely Free/Open. In this way, NeuroML supports #FAIR (Findability, Accessibility, Interoperability, and Reusability) principles, thus promoting open, transparent and reproducible science. 8/x
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#NeuroML is a global community initiative. It is developed by an elected Editorial Board and overseen by a Scientific Committee. All the software/documentation/models produced in NeuroML are completely Free/Open. In this way, NeuroML supports #FAIR (Findability, Accessibility, Interoperability, and Reusability) principles, thus promoting open, transparent and reproducible science. 8/x
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#NeuroML is a global community initiative. It is developed by an elected Editorial Board and overseen by a Scientific Committee. All the software/documentation/models produced in NeuroML are completely Free/Open. In this way, NeuroML supports #FAIR (Findability, Accessibility, Interoperability, and Reusability) principles, thus promoting open, transparent and reproducible science. 8/x
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You can also create new model elements if existing ones aren’t enough AND because #NeuroML is designed to be modular and hierarchical, ALL model elements are independent and can be reused in any NeuroML models. See the full specification here: https://docs.neuroml.org/Userdocs/Specification.html 6/x
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You can also create new model elements if existing ones aren’t enough AND because #NeuroML is designed to be modular and hierarchical, ALL model elements are independent and can be reused in any NeuroML models. See the full specification here: https://docs.neuroml.org/Userdocs/Specification.html 6/x
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You can also create new model elements if existing ones aren’t enough AND because #NeuroML is designed to be modular and hierarchical, ALL model elements are independent and can be reused in any NeuroML models. See the full specification here: https://docs.neuroml.org/Userdocs/Specification.html 6/x
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#NeuroML provides a curated set of model elements for researchers to use. This includes simpler single compartment cells (integrate and fire, Izhikevich, and so on), but also bits required to build detailed multi-compartmental cells (Hodgkin Huxley and Kinetic scheme ionic conductances), synapse models, networks/projections, and network inputs such as spike trains and pulse generators.
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#NeuroML provides a curated set of model elements for researchers to use. This includes simpler single compartment cells (integrate and fire, Izhikevich, and so on), but also bits required to build detailed multi-compartmental cells (Hodgkin Huxley and Kinetic scheme ionic conductances), synapse models, networks/projections, and network inputs such as spike trains and pulse generators.
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#NeuroML provides a curated set of model elements for researchers to use. This includes simpler single compartment cells (integrate and fire, Izhikevich, and so on), but also bits required to build detailed multi-compartmental cells (Hodgkin Huxley and Kinetic scheme ionic conductances), synapse models, networks/projections, and network inputs such as spike trains and pulse generators.
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#NeuroML provides a simulator independent standard and software tools. The idea is that researchers can use NeuroML to build their models, and these models will “just run” in any of the supported simulators. So, researchers only need to learn how to use NeuroML and then choose what simulator they want to run their model in. NeuroML-compliant tools will take care of the rest, “under the hood”. 4/x
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I use pushd/popd quite a bit to navigate directories. I've also been using #fzf quite a bit with and without #vim. It's Alt + C mapping for the terminal is awesome. So I went ahead and created a new Alt + P mapping that does the same thing but uses #pushd instead of #cd. Here's the tweak to my `~/.bashrc` if anyone else wants to do it too:
https://github.com/sanjayankur31/100_dotfiles/commit/ae2a168ce18f9c849244e75a0fc94678f760dd0c
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I use pushd/popd quite a bit to navigate directories. I've also been using #fzf quite a bit with and without #vim. It's Alt + C mapping for the terminal is awesome. So I went ahead and created a new Alt + P mapping that does the same thing but uses #pushd instead of #cd. Here's the tweak to my `~/.bashrc` if anyone else wants to do it too:
https://github.com/sanjayankur31/100_dotfiles/commit/ae2a168ce18f9c849244e75a0fc94678f760dd0c
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I use pushd/popd quite a bit to navigate directories. I've also been using #fzf quite a bit with and without #vim. It's Alt + C mapping for the terminal is awesome. So I went ahead and created a new Alt + P mapping that does the same thing but uses #pushd instead of #cd. Here's the tweak to my `~/.bashrc` if anyone else wants to do it too:
https://github.com/sanjayankur31/100_dotfiles/commit/ae2a168ce18f9c849244e75a0fc94678f760dd0c
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PSA @fedora folks, to use #Discourse (#AskFedora and #FedoraDiscussion) on your #QTWebEngine based browsers like #Qutebrowser and #Falkon, pass `enable-experimental-web-platform-features` in the `qt.args` (for Qutebrowser, not sure what it is for Falkon):
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PSA @fedora folks, to use #Discourse (#AskFedora and #FedoraDiscussion) on your #QTWebEngine based browsers like #Qutebrowser and #Falkon, pass `enable-experimental-web-platform-features` in the `qt.args` (for Qutebrowser, not sure what it is for Falkon):