Invasion of the oak people. Hitched a ride on the pseudo-balloons (not actually) from China.

This is an ornate spiny lobster (Panulirus ornatus). Apparently this is what it takes to impress the girls in lobster world.... Works for me.

@AngelaPreston 🙂 It’s based on a new model which combines OpenJourney (which is an attempt on the StableDiffusion side to get the MidJourney aesthetic …) and something else which, if I recall correctly, was also supposed to give great visuals. Not quite sure it’s up to MidJourney levels, but the visuals did improve from the bland stuff I was getting earlier for “I Shall Wear Midnight” with the standard StableDiffusion model …

And I've been let go.

So uh.

Anyone in Philly Hiring a Data Analyst, let me know.

Now that I've got a working workflow for StableDiffusion image generation again, I can finally get back to the long neglected #DiscWorld novel title series ...

Yesterday's prompt was: "I Shall Wear Midnight"

Not much DiscWorld-iness in the images, but they all were suitably dark to represent midnight, I guess 😛

#AIArt #StableDiffusion #DeepLearning #MachineLearning #CV #AI #DiscWorld
Prompt: “I Shall Wear Midnight”…
Prompt: “I Shall Wear Midnight”…
Prompt: “I Shall Wear Midnight”…
Prompt: “I Shall Wear Midnight”…

And that’s the end of another day of paper reading — some really interesting (to me at least) stuff today but only 7 papers in the cs.CV category (and one outside) boosted from a total of 97 papers on arXiv.org today …

#AI #CV #NewPapers #DeepLearning #MachineLearning

"Exploiting Cultural Biases via Homoglyphs in Text-to-Image Synthesis. (arXiv:2209.08891v2 [cs.CV] UPDATED)" — An interesting look at how replacing Latin characters with non-Latin (visual) equivalents, generative models reflect cultural stereotypes and biases in their generated images.

Paper: http://arxiv.org/abs/2209.08891

#AI #CV #NewPaper #DeepLearning #MachineLearning

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Example of homoglyph manipulati…

"Dark solitons in Bose-Einstein condensates: a dataset for many-body physics research. (arXiv:2205.09114v2 [cond-mat.quant-gas] UPDATED)" — A dataset of over 1.6×10⁴ experimental images of Bose-Einstein condensates containing solitonic excitations to enable machine learning (ML) for many-body physics research.

Paper: http://arxiv.org/abs/2205.09114

#AI #CV #NewPaper #DeepLearning #MachineLearning

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(a)–(c) Raw data from which dat…

"I²SB: Image-to-Image Schrödinger Bridge. (arXiv:2302.05872v1 [cs.CV])" — A new class of conditional diffusion models that directly learn the nonlinear diffusion processes between two given distributions.

Paper: http://arxiv.org/abs/2302.05872

#AI #CV #NewPaper #DeepLearning #MachineLearning

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Outputs of our proposed Image-t…

"Heckerthoughts" — A manuscript going through the basic concepts central to AI and Machine Learning where the author claims that some concepts he included are missing from modern ML courses. Conversational style, anecdotal, and not too long at 54 pages. Worth reading …

Paper: https://arxiv.org/abs/2302.05449

#AI #NewPaper #DeepLearning #MachineLearning

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The “burst” of emails that prom…

"Stochastic Surprisal: An inferential measurement of Free Energy in Neural Networks. (arXiv:2302.05776v1 [cs.LG])" — A framework that allows for action during inference in supervised neural networks.

Paper: http://arxiv.org/abs/2302.05776
Code: https://github.com/olivesgatech/Stochastic-Surprisal

#AI #CV #NewPaper #DeepLearning #MachineLearning

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Stochastic surprisal answers co…

"Adding Conditional Control to Text-to-Image Diffusion Models. (arXiv:2302.05543v1 [cs.CV])" — A method to control pretrained large diffusion models to support additional input conditions which can be used to augment existing generative models such as StableDiffusion by enabling conditional inputs like edge maps, segmentation maps, keypoints, etc.

Paper: http://arxiv.org/abs/2302.05543
Code: https://github.com/lllyasviel/ControlNet

#AI #CV #NewPaper #DeepLearning #MachineLearning

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Control Stable Diffusion with C…

"MaskSketch: Unpaired Structure-guided Masked Image Generation. (arXiv:2302.05496v1 [cs.CV])" — An image generation method that uses a guiding sketch to generate realistic images that match the structure of the sketch.

Paper: http://arxiv.org/abs/2302.05496

#AI #CV #NewPaper #DeepLearning #MachineLearning

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Given an input sketch and its c…

"Element-Wise Attention Layers: an option for optimization. (arXiv:2302.05488v1 [cs.LG])" — A new method of attention mechanism which uses matrices multiplications and has shown 92% accuracy and a 97% reduction in parameters for the Fashion MNIST dataset.

Paper: http://arxiv.org/abs/2302.05488

#AI #CV #NewPaper #DeepLearning #MachineLearning

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The outputs of the attention mo…

A total of 97 papers in the cs.CV category on arXiv.org today — 40 new, 57 updated.

That seems a little daunting today since there’s other stuff I want to work on too, but I guess we’ll just have to see how many interesting papers there are out of the lot?

#AI #CV #NewPapers #DeepLearning #MachineLearning

Morning all,

I wish you all a happy Monday.

A shot of a beautiful little Robin for todays image, the local nature reserve has many of these at this time of year, and they are all fearless, happy to get really close.

#DailyPhoto #Photography #Nautre #Robin

in another entry for #OopsAllMourningDoves i give you this very nice mourning dove sitting on the edge of a platform bird feeder. all birds are good birds, even the ones that may normally get overlooked or are rather common where you are

#birds #BirdsOfMastodon #BirdPhotography #MourningDove

This is reasonable.
https://patreon.com/lowqualityfacts

New preprint "Opaque prior distributions in Bayesian latent variable models", where we describe issues with priors that are easy to overlook and that can lead to incorrect or irreproducible results. The paper is informed by mistakes that I've made over the years. #sem #bayes #mcmc #stan

https://arxiv.org/abs/2301.08667

Noa Kallioinen gave a short tutorial on how to do prior and likelihood sensitivity analysis (prior sensitivity can be due to prior-likelihood conflict or due to a weak likelihood) with `priorsense` R package in Bayes@Lund and the 18min video is now available https://www.youtube.com/watch?v=TBXD3HjcIps&list=PLUEhQLNNQrgndd7_ZY-U5x9lYssl25jmd&index=13

#Bayes #Stan #RStats