netspractice / network-science

Practical assignments for the network science course

Practical Assignments for Network Science

This repository contains practical assignments on network analysis. All assignments are presented as Jupyter notebooks, that can be done by writing code instead of the line

# YOUR CODE HERE

All notebooks contain test cells with assert statements that help you understand whether your code is correct.

Topics:

1. Introduction to Network Science

Here are also descriptions of some competitions held among students to solve practical tasks on graphs:

1. TBA

Lecture materials: http://leonidzhukov.net/hse/2023/networkscience/

Youtube channel with records of lectures: https://youtube.com/playlist?list=PLriUvS7IljvkGesFRuYjqRz4lKgodJgh2

network-science's Issues

Error in the gnn_solution.ipynb file

The gnn-cloud-manufacturing /notebooks/gnn_solution.ipynb file contains the following error:

with torch.no_grad():
2 prob = model(graph)
----> 3 v, u = model.dec.sample(graph, prob)
'DotProductDecoder' object has no attribute 'sample'.

This class is declared in the file gnn-cloud-manufacturing/cloudmanufacturing/graphconv.py

Epidemics on graphs: add meaningful and random tolerance asserts

All tasks.

Community detection 2: task 7, add asserts to check randomness

The algorithm should select a random label among the most common in neighborhood