Blog

• (2023-04-27) A deep dive into conditional variational autoencoders

  An excerpt from my PhD thesis. We discuss various difficulties involved in correctly training variational autoencoders, as well as elucidate their behaviour from a theoretical perspective.

• (2023-04-15) Vicinal distributions as a statistical view on data augmentation

  An excerpt from my PhD thesis. I introduce data augmentation through the lens of vicinal distributions, and introduce mixup augmentation as a multi-sample generalisation of it.

• (2023-03-20) My notes and derivations for SMLDs

• (2023-01-27) Techniques for label conditioning in Gaussian denoising diffusion models

  A discussion of three recently-proposed conditional variants for Gaussian diffusion probabilistic models -- classifier-based guidance, classifier-free guidance, and the conditional ELBO (evidence lower bound).

• (2022-09-24) Learning the conditional prior over classes for image diffusion

  My implementation of a conditional diffusion model for speech enhancement, demonstrated for images on the MNIST dataset. Unlike other conditional formulations which use classifier-style guidance, this proposes a conditional variant of the ELBO.

• (2022-08-02) The obsession with SOTA needs to stop

• (2022-07-24) Towards a more sane Mac OS user experience, and I am late to the party

• (2022-07-11) My notes on discrete denoising diffusion models (D3PMs)

  My notes on D3PMs. It includes derivations for the two main equations presented in their work.

• (2021-08-17) A somewhat mathematical introduction to Gaussian and Laplace autoencoders

• (2021-06-28) Training GANs the right way