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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About Me
About me
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Publications
Publications
Posts
Interval Bound Propagation 102: From Theory to Code
Published:
In Interval Bound Propagation 101 I derived the general IBP machinery: interval arithmetic over matrices via Rump’s algorithm, and how to propagate those bounds through a feed-forward network layer by layer. This post grounds that theory in a small worked example: a concrete network, a from-scratch numpy implementation of IBP, and the visualizations that fall out of it.
Interval Bound Propagation 101
Published:
The purpose of this post is to explain the basics of the Interval Bound Propagation (IBP) method. It is powerful tool which allows to provide guarantees about output ranges of a neural network. I mostly follow the notation from deep reinforcement learning (RL), therefore the typical neural network for which I want to compute bounds is a neural policy.
Incremental Reinforcement Learning
Published:
From https://www.nature.com/articles/s42256-022-00568-3 (which is for supervised learning)
Variational Inference 101
Published:
Say you want to estimate a distribution of a latent vector $Z$ based on observations $X$. You can do that with variational inference!
Multi-armed Bandits
Published:
Conspectus of Sutton & Barto “Reinforcement Learning: An Introduction”
Introduction to Reinforcment Learning
Published:
Conspectus of Sutton & Barto “Reinforcement Learning: An Introduction”
Introduction to Reinforcment Learning: Markov Process
Published:
One of the core concepts of basic reinforcement learning are a Markov Process and a Markov Reward Process.
publications
teaching
Teaching Assistant in Calculus & Linear Algebra
Undergraduate course, Higher School of Economics, 2016
Gave weekly tutorials to three international students who successfully passed their Calculus and Linear Algebra exams.
Teaching Assistant in Macroeconomics
Undergraduate course, Higher School of Economics, 2018
Gave weekly tutorials on macroeconomic models to groups of 60-70 students.
Data Structures & Algorithms
Graduate course, Imperial College London, 2024
Provided tutorials and lab support to the MSc Business Analytics students.
Reinforcement Learning
Graduate course, Imperial College London, 2024
Provided lab support and coursework marking at the Department of Computing.
Data Structures & Algorithms
Graduate course, Imperial College London, 2025
Provided tutorials and lab support to the MSc students.