When looking for a new job, having a referral at a promising company may be crucial (since it may be difficult to pass hr screening these days). Ideally, a referral is somebody you know, however, a person from the same university or town is also ok. At first, I was trying to search for potential referrals on LinkedIn and got frustrated quite fas... Read more 29 Nov 2022 - 2 minute read
This post continues the series of posts on Cascade Models. From time to time I experiment with this type of models on graphs. Last month Misha Chertkov formulated the following question to me: “Is there a closed-form formula (or an efficient algorithm) that computes the most probable final state of a cascade model?”. Moreover: “What if we want ... Read more 11 Nov 2022 - 3 minute read
In this short post, I want to define Shared Risk Link Groups and illustrate this with an interactive plot using Grave and Networkx. Shared Risk Groups Shared Risk (Resource) Group is an important concept in Network Theory. This concept may arise in different types of networks (IP, optical, MPLS). Generally, there are two networks to be conside... Read more 18 Aug 2022 - 2 minute read
My other hobby is learning about blockchain technology, and I like to learn by experiment. In this post, I will use API by Blockchain.com to get raw block data in JSON format. This API has a request limit of a maximum of 1 request every 10 seconds. A more efficient way would be running a bitcoin node; however, this is not always a convenient wa... Read more 31 Jul 2022 - 3 minute read
In this short post, I want to illustrate some graph clustering/partitioning ideas. First, I generate a random Gabriel graph with 50 vertices; how to generate such graphs I described in the previous post. First, we will need the following imports: from geometric import random_gabriel_graph import networkx as nx import numpy as np from gensim.m... Read more 23 Jul 2022 - 2 minute read