Daphne Cornelisse's repositories
Fastai-Planet-Files
This notebook explains how to import the planet files for notebook 2 -
Transients
Capstone project studying the distribution of transients in RRNN
Advanced_machine_learning
adv ml course autumn 2020
behavenet
Toolbox for analyzing behavioral videos and neural activity
brian_projects
Collection of projects in brian
Computational_neuroscience
Everything comp neuro
CURBD
Code to train and analyze multi-region data-constrained RNNs and perform Current-Based Decomposition (CURBD)
daphnecor
Config files for my GitHub profile.
daphnecor.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
jraph
A Graph Neural Network Library in Jax
nest-simulator
The NEST simulator
NeuroAnalysis
Assignments for the Neuro-analysis course 2021
neuronaldynamics-exercises
Python exercises accompanying the book "Neuronal Dynamics"
PyalData
Repository for the Python implementation of the TrialData analysis library.
Python_for_DataScience
This contains all the links to colab notebooks used in the Python for Data Science Bootcamp by Turing Students Rotterdam.
Pytorch_collections
Collection of Pytorch notebooks and notes
TME
This code package is for the Tensor-Maximum-Entropy (TME) method. This method generates random surrogate data that preserves a specified set of first and second order marginal moments of a data tensor, which makes it well equipped to test for the null hypothesis that a structure in data is an epiphenomenon of these specified set of primary features of the data tensor. The random surrogate data are sampled from a maximum entropy distribution. This distribution unlike traditional maximum entropy method have constraints on the marginal first and second moments of the tensor mode.
tmux-config
Defend your .tmux.conf at all costs
Variational-Autoencoder-pytorch
Implementation of a convolutional Variational-Autoencoder model in pytorch.