diffusion – Page 2 – Andrew Fairless, Ph.D.

What I Read: Physical Process, Generative AI

By Andrew Fairless on October 31, 2023October 5, 2023

https://www.quantamagazine.org/new-physics-inspired-generative-ai-exceeds-expectations-20230919/ The Physical Process That Powers a New Type of Generative AISteve Nadis9/19/23 10:15 AM “Some modern image generators rely on the principles of diffusion to create images. Alternatives basedContinue readingWhat I Read: Physical Process, Generative AI

What I Read: Perspectives on diffusion

By Andrew Fairless on August 30, 2023July 30, 2023

https://sander.ai/2023/07/20/perspectives.html Perspectives on diffusionSander DielemanJuly 20, 2023 “Diffusion models appear to come in many shapes and forms…. these various perspectives each reveal new connections and are a breeding ground forContinue readingWhat I Read: Perspectives on diffusion

What I Read: Modern AI Art

By Andrew Fairless on March 6, 2023January 9, 2023

https://www.quantamagazine.org/the-physics-principle-that-inspired-modern-ai-art-20230105/ The Physics Principle That Inspired Modern AI ArtAnil AnanthaswamyJanuary 5, 2023 “Diffusion models generate incredible images by learning to reverse the process that, among other things, causes ink toContinue readingWhat I Read: Modern AI Art

What I Read: Poisson Flow Generative Models

By Andrew Fairless on January 5, 2023November 5, 2022

https://www.assemblyai.com/blog/an-introduction-to-poisson-flow-generative-models/ An Introduction to Poisson Flow Generative ModelsRyan O’ConnorDeveloper EducatorOct 26, 2022 “Poisson Flow Generative Models (PFGMs) are a new type of generative Deep Learning model, taking inspiration from physicsContinue readingWhat I Read: Poisson Flow Generative Models

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: Illustrated Stable Diffusion

By Andrew Fairless on November 29, 2022October 20, 2022

https://jalammar.github.io/illustrated-stable-diffusion/ The Illustrated Stable DiffusionJay AlammarVisualizing machine learning one concept at a time. “The ability to create striking visuals from text descriptions has a magical quality to it and pointsContinue readingWhat I Read: Illustrated Stable Diffusion

What I Read: Annotated Diffusion Model

By Andrew Fairless on August 1, 2022June 27, 2022

https://huggingface.co/blog/annotated-diffusion The Annotated Diffusion ModelPublished June 7th, 2022Niels RoggeKashif Rasul “In this blog post, we’ll take a deeper look into Denoising Diffusion Probabilistic Models… as researchers have been able toContinue readingWhat I Read: Annotated Diffusion Model

What I Read: Beyond Message Passing, Graph Neural Networks

By Andrew Fairless on June 6, 2022May 23, 2022

https://thegradient.pub/graph-neural-networks-beyond-message-passing-and-weisfeiler-lehman/ Beyond Message Passing: a Physics-Inspired Paradigm for Graph Neural NetworksMichael Bronstein07.May.2022 “…the “node and edge-centric” mindset of current graph deep learning schemes imposes strong limitations… we propose physics-inspired “continuous”Continue readingWhat I Read: Beyond Message Passing, Graph Neural Networks

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

Tag: diffusion