Blogs, Article & Tutorials – Ayan Das

Match flows, not scores

Deep Learning

Generative Models

Diffusion

Fundamentals of flow matching, path straightening and reflow.

Building Diffusion Model’s theory from ground up

Deep Learning

Generative Models

Diffusion

Differential Equation

Explains how diffusion model’s theory can be built from ground-up with fundamental principles

An introduction to Diffusion Probabilistic Models

Deep Learning

Generative Models

Diffusion

The theoretical fundamentals of Diffusion Models & their connection with SDEs

Generative modelling with Score Functions

Deep Learning

Generative Models

Diffusion

Energy based models

Basics of score function and using it for generative modelling.

Differentiable Programming: Computing source-code derivatives

Compilers/Interpreter

Deep Learning

An introduction to the realm of DiffProg with example in Julia Zygote.

Energy Based Models (EBMs): A comprehensive introduction

Graphical Models

Energy based models

An introductory article on EBM’s theoretical fundamental, including CD and Boltzmann machine family.

Introduction to Probabilistic Programming

Graphical Models

Deep Learning

Variational Methods

Generative Models

A theoretical understading of probabilistic programming and a popular tool called pyro

Patterns of Randomness

Generative Art

Few examples (random walk, dynamical system, fourier & mandelbrot) of mathematial art using the power of randomness.

Neural Ordinary Differential Equation (Neural ODE)

Differential Equation

Deep Learning

A conceptual introduction to Neural Ordinary Differential Equation, a new “continuous depth” architecture.

Foundation of Variational Autoencoder (VAE)

Deep Learning

Variational Methods

Graphical Models

Generative Models

Building on earlier article on VI, we describe how VAE is conceptualized.

Directed Graphical Models & Variational Inference

Variational Methods

Graphical Models

Deep Learning

Introductory article about VI, making way of Variational Autoencoders.

TeX & family : The Typesetting ecosystem

Typesetting

An introductory article on the typesetting ecosystem, specifically TeX and its derivates

Speeding up iostreams in C++

C++

Language

Recipes for speeding up I/O operations in C++

Rohan Mark Gomes, Ayan Das

Static and Dynamic linking

C++

Language

A broad view of C++ linking

Rohan Mark Gomes, Ayan Das

Advanced Python: Bytecodes and the Python Virutal Machine (VM) - Part I

Python

Compilers/Interpreter

Language

Over the years, Python has become one of the major general purpose programming language that the industry and academia care about. But even with a vast community around the…

Deep Learning at scale: Setting up distributed cluster

Distributed Computing

Deep Learning

A hands-on tutorial for setting up a cluster of machines for distributed computation.

Deep Learning at scale: The “torch.distributed” API

Distributed Computing

Deep Learning

With a distributed setup ready, we now explore a low-level API for distributed computing.

Intermediate Python: Generators, Decorators and Context managers - Part II

Python

Language

In my previous post, I laid out the plan for couple of tutorials in the same series about intermediate level Python. This series of posts are intended to introduce some of…

Intermediate Python: Generators, Decorators and Context managers - Part I

Python

Language

Welcome to the series of Intermediate Python tutorials. Before we begin, let me make it very clear that this tutorial is NOT for absolute beginners. This is for Python progra…

CapsNet architecture for MNIST

Deep Learning

Equipped with the idea of capsules, we explore an architecture for MNIST.

An intuitive understanding of Capsules

Deep Learning

Explanation of the idea of capsules by G. Hinton.