generative adversarial network – Andrew Fairless, Ph.D.

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: 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: Game theory for large-scale data analysis

By Andrew Fairless on June 7, 2021May 14, 2021

https://deepmind.com/blog/article/EigenGame 06 May 2021Game theory as an engine for large-scale data analysisBrian McWilliamsIan GempClaire Vernade “…we reformulated principal component analysis (PCA)… as a competitive multi-agent game we call EigenGame. PCAContinue readingWhat I Read: Game theory for large-scale data analysis

What I Read: Adversarial Neural Cryptography

By Andrew Fairless on May 18, 2021May 1, 2021

https://pub.towardsai.net/what-is-adversarial-neural-cryptography-70b461c7db88?gi=3bf97cbeefd What is Adversarial Neural Cryptography?The novel approach combines GANs and cryptography in a single, powerful security method.Jesus RodriguezApr 19 “Somewhere between anonymization methods and homomorphic encryption, we find aContinue readingWhat I Read: Adversarial Neural Cryptography

What I Read: Zero-Shot Learning

By Andrew Fairless on May 6, 2021April 13, 2021

https://www.kdnuggets.com/2021/04/zero-shot-learning.html Zero-Shot Learning: Can you classify an object without seeing it before?Developing machine learning models that can perform predictive functions on data it has never seen before has become anContinue readingWhat I Read: Zero-Shot Learning

What I Read: Adversarial generation of extreme samples

By Andrew Fairless on March 19, 2021March 7, 2021

https://aihub.org/2020/10/01/adversarial-generation-of-extreme-samples/ Adversarial generation of extreme samplesby Lucy SmithOctober 1, 2020 “…existing GAN-based methods tend to generate typical samples.. the authors seek to design deep learning-based models that can generate samplesContinue readingWhat I Read: Adversarial generation of extreme samples

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

Tag: generative adversarial network