The world is a little less bright with the passing of Terry Sehr. From my professor at @CCEmergentMedia to a collaborator in The Illumination Collective, Terry inspired us all with his quiet reverential wonder of the natural mechanisms inherent in digital art. You will be missed.
Terry's generative snowflake, from our installation at ECHO Aquarium for Burlington's Highlight NYE celebration. A tribute to Snowflake Bentley:

Terry's Self-Portrait from 2016: "the artist projects his views and interests onto social media, and then reconstructs an image of himself from his own digital imprint."

From our forest installation in Randolph, Vermont, Terry's Generative squiggles on a translucent black mesh, with my lamp installation amongst the trees in the background

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More from @artistjaneadams

10 Jun
Creating a thread of mega-threads for my pinned tweet to add to periodically. Adding "Twitter Novelist" to my CV. Then taking a deep breath and walking outside 🌲🌄🌳
Read 5 tweets
10 Jun

Sirius: A Mutual Information Tool for Exploratory Visualization of Mixed Data

by @artistjaneadams @todddeluca @ChrisDanforth
@peterdodds of @uvmcomplexity and Yuhang Zheng, Konstantinos Anastasakis, Boyoon Choi, Allison Min, and Michael Bessey of @massmutual
Through a partnership with @mmdatascience as the MassMutual Center of Excellence in Complex Systems and Data Science at @uvmcems, we had a question:

How can we create better visualization tools for high-dimensional mixed data exploration to better understand complex health?
Read 40 tweets
27 Apr
This is an important subject matter, but PLEASE, researchers: typing a term into google and counting the *number of search results* is not the same as finding the search term frequency. Thread:
1) These results appear to have been found by searching (subjectively selected) phrases, *without quotes*, with "before:" and "after:" modifiers. MOST terms will show a significant increase in result count because:
2) Without quotes means that any articles containing some combination of these words will be shown. Example: 183 million results! But what is returned? Image
Read 10 tweets
17 Feb

Presenting @compstorylab Story Time today: "From Liminal to Latent Space: GANs as a Medium"

I'll be sharing my experiments with Generative Adversarial Networks in a new music video collaboration with @alexawoodward - album out 3/5!

Thread to follow 🧵
GAN stands for "Generative Adversarial Network". Two neural nets, a generator and a discriminator, work together.

By switching on or off nodes in the generator network, it’s possible to 'segment' the GAN to find out which node controls which aspect of the image (1/n)
The Fréchet Inception Distance (F.I.D) score measures the difference between two image datasets. Lower FID scores mean more similarity. As a GAN trains, the FID score (hopefully) decreases.… (2/n)
Read 47 tweets

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