I was curious whether it would be possible to let #GANs generate samples conditioned on a specific input type. I wanted the GAN to generate samples of a specific digit, resembling a personal poor man’s mini #DALLE 😅. And indeed, I found a GAN architecture, that allows so-called #ConditionalGANs 💫

🌎 https://www.fabriziomusacchio.com/blog/2023-07-30-cgan/

#MachineLearning #GenerativeAdversarialNetworks

The #Wasserstein #metric (#EMD) can be used, to train #GenerativeAdversarialNetworks (#GANs) more effectively. This tutorial compares a default GAN with a #WassersteinGAN (#WGAN) trained on the #MNIST dataset.

🌎 https://www.fabriziomusacchio.com/blog/2023-07-29-wgan/

#MachineLearning

LEAD: Min-Max Optimization from a Physical Perspective

Reyhane Askari Hemmat, Amartya Mitra, Guillaume Lajoie, Ioannis Mitliagkas

Action editor: Francisco Ruiz.

https://openreview.net/forum?id=vXSsTYs6ZB

#gans #gan #adversarial

New #FeaturedCertification:

LEAD: Min-Max Optimization from a Physical Perspective

Reyhane Askari Hemmat, Amartya Mitra, Guillaume Lajoie, Ioannis Mitliagkas

https://openreview.net/forum?id=vXSsTYs6ZB

#gans #gan #adversarial

3D-Aware Video Generation

Sherwin Bahmani, Jeong Joon Park, Despoina Paschalidou et al.

Action editor: Mathieu Salzmann.

https://openreview.net/forum?id=SwlfyDq6B3

#gans #generative #3d

'Euler-Lagrange Analysis of Generative Adversarial Networks', by Siddarth Asokan, Chandra Sekhar Seelamantula.

http://jmlr.org/papers/v24/20-1390.html

#gans #generative #adversarial

Insilico Medicine Sees Potential Quantum Advantage in Using Quantum Generative Adversarial Networks in Generative Chemistry https://thequantuminsider.com/?p=2355468 #Quantum_Computing_Business #Research #Alán_AspuruGuzik #drug_discovery #Foxconn #GANs #Generative_Adversarial_Networks #Hon_Hai Research_Institute #Insilico_Medicine #Journal_of_Chemical_Information_and_Modeling #MinHsiu_Hsieh #MolGAN #quantum_advantage #quantumdaily Insider Brief Insilico Medicine used quantum computing and genera

@mamund the interesting thing about #GANs is that they're trained by simulating two competing networks- the one #OpenAI refers to here is called the "discriminator" network. You *have to* create this detection tool as a byproduct of creating the "generator" network.
The conversation should not be about corporates offering these as 'gifts' to the world; but rather why governments do not require them to be disseminated along with the generators as a matter of moral obligation to the public.

LEAD: Min-Max Optimization from a Physical Perspective

https://openreview.net/forum?id=vXSsTYs6ZB

#gans #gan #adversarial

Private GANs, Revisited

https://openreview.net/forum?id=9sVCIngrhP

#gans #gan #private

Regularized Training of Intermediate Layers for Generative Models for Inverse Problems

Sean Gunn, Jorio Cocola, PAul HAnd

https://openreview.net/forum?id=cKsKXR28cG

#gans #gan #generative

3D-Aware Video Generation

https://openreview.net/forum?id=SwlfyDq6B3

#gans #generative #3d

'A Relaxed Inertial Forward-Backward-Forward Algorithm for Solving Monotone Inclusions with Application to GANs', by Radu I. Bot, Michael Sedlmayer, Phan Tu Vuong.

http://jmlr.org/papers/v24/20-267.html

#gans #generative #variational

Having a lot of fun with #deeplearning and #computervison .

Tried out the single shot detection algorithm on a video clip of me walking my dog biscuit on the beach.

With the rise in popularity of #ChataGPT, #DALLE2, #midjourney and #StableDiffusion, I'm interested to learn more about generative networks so my next computer vision project will be around #GANs.

If you have any recommended papers or website links on the topic, please share!

EdiBERT: a generative model for image editing

Thibaut Issenhuth, Ugo Tanielian, Jeremie Mary, David Picard

https://openreview.net/forum?id=GRBbtkW3Lp

#generative #gans #encoders

Art zombies seed 3011. Generated from my custom Glitch Face StyleGAN model blended with Wikiart #aiart #aiartist #GANs #MastoArt

'An Error Analysis of Generative Adversarial Networks for Learning Distributions', by Jian Huang, Yuling Jiao, Zhen Li, Shiao Liu, Yang Wang, Yunfei Yang.

http://jmlr.org/papers/v23/21-0732.html

#gans #generative #adversarial

@nolovedeeplearning @emtiyaz @mathieualain @guy

I’m gonna slightly shamelessly self-plug one of our recent works here too, to share my recently found enthusiasm about #ProbabilisticCircuit :)!

Intuitively, we blur the boundaries again & investigate what PCs with differentiable sampling can do, in an effort to compare with #autoencoding, #GANs etc that made generative NNs more prominent.

Paper is available here: https://proceedings.mlr.press/v181/lang22a/lang22a.pdf

With @sbraun & @kerstingAIML