Aadhithya Sankar

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rajini++: The Superstar Programming Language

Introducing rajini++, an esoteric programming language based on the dialogues of superstar Rajinikanth. The syntax and keywords used in…

May 17, 2022

rajini++: The Superstar Programming Language

May 17, 2022

Create your own programming in 10 minutes!

Ever wanted to create your own esolang? With the rajiniPP project you can create one in less than 10 minutes!!!

Jul 15, 2022

Create your own programming in 10 minutes!

Jul 15, 2022

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Published in
TDS Archive

Demystified: Wasserstein GAN with Gradient Penalty

Why is Gradient Penalty better than gradient clipping? What is Gradient Penalty and how do we implement it?

Oct 2, 2021

Demystified: Wasserstein GAN with Gradient Penalty

Oct 2, 2021

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TDS Archive

Principal Component Analysis Part 1: The Different Formulations.

What is Principal Component Analysis? What are the Maximum Variance and Minimum Error formulations of PCA? How do we reduce dimensionality…

Sep 29, 2021

Principal Component Analysis Part 1: The Different Formulations.

Sep 29, 2021

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Real-time Artwork Generation using Deep Learning

Adaptive Instance Normalisation(AdaIN) for Style Transfer between any arbitrary content-style image pair.

Sep 25, 2021

Real-time Artwork Generation using Deep Learning

Sep 25, 2021

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Learning Disentangled Representations with Invertible(Flow-based) Interpretation Networks

What are disentangled representations?

Sep 18, 2021

Learning Disentangled Representations with Invertible(Flow-based) Interpretation Networks

Sep 18, 2021

Published in
TDS Archive

Demystified: Wasserstein GANs (WGAN)

What is the Wasserstein distance? What is the intuition behind using Wasserstein distance to train GANs? How is it implemented?

Sep 17, 2021

Sep 17, 2021

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TDS Archive

A Primer on Atrous Convolutions and Depth-wise Separable Convolutions

What are atrous/dilated and depth-wise separable convolutions? How are the different from standard convolutions? What are their uses?

Sep 15, 2021

A Primer on Atrous Convolutions and Depth-wise Separable Convolutions

Sep 15, 2021