swathianil
PhD candidate in computational neuroscience, University of Freiburg. Visiting PhD, Imperial College London
Imperial College LondonLondon
Pinned Repositories
2021_human_multi_scale_modeling
Precursor to build Nemo-TMS TBS project
2021_rTMS_intensity_review_paper
cookiecutter-pypackage
Cookiecutter template for a poetry-managed Python package.
deeperbrain
GithubCourse
Harry-Potter-Book-Analysis
Repo to explore and learn methods to analyse and visualise harry potter book series
hello-world
Because, how could I not?
homeostatic_structural_plasticity_rTMS
This reporsitory hosts simulation files, data and plotting notebooks supporting the preprint 'Repetitive transcranial magnetic stimulation (rTMS) triggers dose-dependent homeostatic rewiring in recurrent neuronal networks' by Anil et.al., 2023.
Housing-Price-Prediction-Random-Forest
Logistic-Regression-Breast-Cancer-Wisconsin-Diagnostic-
swathianil's Repositories
swathianil/2021_rTMS_intensity_review_paper
swathianil/2021_human_multi_scale_modeling
Precursor to build Nemo-TMS TBS project
swathianil/cookiecutter-pypackage
Cookiecutter template for a poetry-managed Python package.
swathianil/deeperbrain
swathianil/GithubCourse
swathianil/Harry-Potter-Book-Analysis
Repo to explore and learn methods to analyse and visualise harry potter book series
swathianil/hello-world
Because, how could I not?
swathianil/homeostatic_structural_plasticity_rTMS
This reporsitory hosts simulation files, data and plotting notebooks supporting the preprint 'Repetitive transcranial magnetic stimulation (rTMS) triggers dose-dependent homeostatic rewiring in recurrent neuronal networks' by Anil et.al., 2023.
swathianil/Housing-Price-Prediction-Random-Forest
swathianil/Logistic-Regression-Breast-Cancer-Wisconsin-Diagnostic-
swathianil/nest-simulator
The NEST simulator: SP test
swathianil/NMA_deeplearning
swathianil/ORKG
swathianil/SyNCoPy_solution
Two solutions to the SyNCoPy code challenge: checksum algorithm for tabular data
swathianil/TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)