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I am trying to reproduce figure 1 from the paper:
I've found the code in` fig:latent-rotation/visualize.ipynb` and am attempting to get it to work. IIUC - it appears to assume that pre-baked mo…
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https://arxiv.org/abs/1708.04692
> In this paper, we propose a novel application of Generative Adversarial Networks (GAN) to the synthesis of cells imaged by fluorescence microscopy. Compared to na…
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It is mentioned multiple times in the paper that all tokens from the same scale r are generated in parallel. Did I overlook or there is actually little description about how to generate tokens in para…
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- [Fast-Paced Multiplayer (Gabriel Gambetta)](http://www.gabrielgambetta.com/fpm1.html)
- [Defeating Lag With Cubic Splines (Nick Caldwell)](http://www.gamedev.net/page/resources/_/technical/multiplay…
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https://devblogs.nvidia.com/parallelforall/photo-editing-generative-adversarial-networks-2/
基于nvidia-digits的实现
https://github.com/gheinrich/DIGITS-GAN/blob/DIGITS-GAN-v0.1/examples/gan/README.md
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Feature: experiment with _z_ which are a mix of normals, censored normals, binomials, and categoricals.
Typically, in almost all GANs, the original _z_ random noise is just a bunch of Gaussian vari…
gwern updated
3 years ago
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用 mixup 增强 group fairness metrics 的泛化性,通过两个 sensitive group 样例的渐近插值,搭建一个逐步的变换过程来连接彼此(图示很明白),帮助模型学习的更公平。以往的方法都依赖于数据,本文方法与数据无关,可跨模态、跨数据等等。搞了点理论证明,在表格、视觉和文本的 fairness 数据集上实验了,有效果。
总的来说,就是在二分类上用了mixup,…
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Hello @b-remy and @EiffL. As we discused, the [last code version](https://github.com/JonnyyTorres/Galsim_JAX/blob/b1c4cc3b61657aa97647dd5e863c920cb8608d4d/VAE_SD_C.py) contains the convolution with th…
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Thanks for getting it working, love it!
Using it I've come up with a couple of improvements that could enhance the experience :
1- Option to export as video with ffmpeg (with options for FPS, ex…
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Hi!
I'm really excited about this implementation of generative audio and have just started training on my gaming GTX 1060 laptop.
My focus is to generate different waveGANs using a dataset out o…