wsojka00

reproducible-neuroimaging

A guide to reproducible neuroimaging research.

wildfires

Cellular automata simulation of forest fires based on Malamud et. al, 1998

01-homework

Homework for Advanced fMRI data course at Nicolaus Copernicus University

02-homework

03-homework

04-homework

05-homework

gaze-following

Code & documentation reporting results obtained when working on a project named "Gaze-following in nonhuman primates" under the supervision of Prof. Peter Thier, Masih Shafiei and Marius Görner at University of Tübingen.

graph_navigation

Open-source code repository where reinforcement learning agents solve grid-maze environment and represent learning process as a graph learning.

phi_gcn

Reward Propagation using Graph Convolutional Networks

wsojka00/phi_gcn

Reward Propagation using Graph Convolutional Networks

wsojka00/gaze-following

Code & documentation reporting results obtained when working on a project named "Gaze-following in nonhuman primates" under the supervision of Prof. Peter Thier, Masih Shafiei and Marius Görner at University of Tübingen.

wsojka00/graph_navigation

Open-source code repository where reinforcement learning agents solve grid-maze environment and represent learning process as a graph learning.

wsojka00/pyclass23

wsojka00/THUS-Torun

wsojka00/all-contributors

✨ Recognize all contributors, not just the ones who push code ✨

wsojka00/Assael2022

Restoring and attributing ancient texts using deep neural networks

wsojka00/bids-specification

Brain Imaging Data Structure (BIDS) Specification

wsojka00/bids-validator

Validator for the Brain Imaging Data Structure

wsojka00/brainiak-tutorials

wsojka00/CaImAn

Computational toolbox for large scale Calcium Imaging Analysis, including movie handling, motion correction, source extraction, spike deconvolution and result visualization.

wsojka00/computational-modelling

Code and website accompanying Farrell & Lewandowsky's (2017) book

wsojka00/cv

wsojka00/EDA-on-Netflix---Data-Literacy-WS2021-22

wsojka00/Electrophysiology-Tutorial-for-Neuroscience

This is a tutorial for key data analysis steps used by neuroscientists - filtering, spike extraction, PCA, clustering, and spectral analysis. It applies to neuroscientists who deal with spikes, LFPs, EEGs and EMGs

wsojka00/FindingLandmarks_a_publication_repository

Repository for the publication "Finding landmarks – an investigation of viewing behavior during spatial navigation in VR using a graph-theoretical analysis approach". Contains all scripts used in the publication, for example the pre-processing pipeline and graph theoretical analysis

wsojka00/gym-minigrid

Minimalistic gridworld package for OpenAI Gym

wsojka00/HodgkinHuxley

Code based on Hodgkin-Huxley spiking neuron model in Python made by @giuseppebonaccorso with additional changes and attempts to understand principles of the model.

wsojka00/KordingLab.github.io

Jekyll page for Kording lab webpage

wsojka00/maze

Generate random, solvable mazes and solve them.

wsojka00/maze-generator

Test code for maze generation

wsojka00/mne-python

MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python

wsojka00/neural_data_science

Contains programming labs and lecture notes for the lecture "Neural Data Science"

wsojka00/neuro-nav

A set of neuroscience inspired navigation and decision making tasks.

wsojka00/PathFinder

Discover optimum path through graphs of costed links

wsojka00/pypillometry

pupillometry with python

wsojka00/Pythia

Restoring ancient text using deep learning: a case study on Greek epigraphy.

wsojka00/PyTrack

wsojka00/reinforcement-learning-implementation

Reinforcement Learning examples implementation and explanation

wsojka00/rl-starter-files

RL starter files in order to immediatly train, visualize and evaluate an agent without writing any line of code