variational autoencoder – Andrew Fairless, Ph.D.

What I Read: KL All You Need

By Andrew Fairless on August 21, 2024June 4, 2024

https://blog.alexalemi.com/kl-is-all-you-need.html KL is All You NeedAlexander A. Alemi2024-01-08 “…the core of essentially all modern machine learning methods is a single universal objective: Kullback-Leibler (KL) divergence minimization…. Understand KL, understand theContinue readingWhat I Read: KL All You Need

What I Read: How diffusion models work

By Andrew Fairless on November 30, 2022October 20, 2022

https://theaisummer.com/diffusion-models/ How diffusion models work: the math from scratchSergios Karagiannakos, Nikolas Adaloglouon2022-09-29 “Diffusion models are a new class of state-of-the-art generative models that generate diverse high-resolution images.”

What I Read: Generative Modeling by Estimating Gradients

By Andrew Fairless on March 7, 2022January 20, 2022

https://yang-song.github.io/blog/2021/score/ Generative Modeling by Estimating Gradients of the Data DistributionAuthor Yang SongDate May 5, 2021 “This blog post gives a detailed introduction to score-based generative models. We demonstrate that thisContinue readingWhat I Read: Generative Modeling by Estimating Gradients

What I Read: Introduction AutoEncoder

By Andrew Fairless on November 15, 2021October 24, 2021

https://www.theaidream.com/post/an-introduction-to-autoencoder-and-variational-autoencoder-vae Introduction to AutoEncoder and Variational AutoEncoder(VAE)Nagesh Singh ChauhanJul 28“In recent years, deep learning-based generative models have gained more and more interest…. we will dive deep into these generative networksContinue readingWhat I Read: Introduction AutoEncoder

What I Read: Diffusion Models

By Andrew Fairless on August 18, 2021July 22, 2021

https://lilianweng.github.io/lil-log/2021/07/11/diffusion-models.html#nice What are Diffusion Models?Jul 11, 2021Lilian Weng“Diffusion models are inspired by non-equilibrium thermodynamics…. Unlike VAE or flow models, diffusion models are learned with a fixed procedure and the latentContinue readingWhat I Read: Diffusion Models

What I Read: Flows for simultaneous manifold learning and density estimation

By Andrew Fairless on December 31, 2020December 20, 2020

https://arxiv.org/abs/2003.13913 Flows for simultaneous manifold learning and density estimationJohann Brehmer, Kyle Cranmer “We introduce manifold-learning flows (M-flows), a new class of generative models that simultaneously learn the data manifold asContinue readingWhat I Read: Flows for simultaneous manifold learning and density estimation

What I Read: Element-wise Active Information Acquisition

By Andrew Fairless on December 4, 2020November 28, 2020

https://arxiv.org/abs/1908.04537 Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian ModelWenbo Gong, Sebastian Tschiatschek, Richard Turner, Sebastian Nowozin, José Miguel Hernández-Lobato, Cheng Zhang “…we introduce the ice-start problem, i.e.,Continue readingWhat I Read: Element-wise Active Information Acquisition

Tag: variational autoencoder