I invented a new generative model and got accepted to ICLR
I invented Discrete Distribution Networks, a novel generative model with simple principles and unique properties, and the paper has been accepted to ICLR2025! Modeling data distribution is challenging; DDN adopts a simple yet fundamentally different approach compared to mainstream generative models (Diffusion, GAN, VAE, autoregressive model): 1. The model generates multiple outputs simultaneously in a single forward pass, rather than just one output. 2. It uses these multiple outputs to approximate the target distribution of the training data. 3. These outputs together represent a discrete…
I invented a new generative model and got accepted to ICLR launched on October 10, 2025 with 656 votes, #11 of 8,178 launches that month and more than 99% of that year's launches. The site was still online in September 2026, 1 year on.
In plain words
Discrete Distribution Networks is a generative model that produces multiple outputs simultaneously in a single forward pass to approximate data distributions, offering a fundamentally different approach from diffusion, GAN, VAE, and autoregressive models. The method uses these multiple outputs to represent a discrete distribution. It is designed for researchers and machine learning practitioners working on generative tasks and supports capabilities like zero-shot conditional generation. The research has been accepted to ICLR 2025.
written from the facts on this page · September 2026
From the sources
Novel Generative Model with Simple Principles and Unique Properties
Left: Illustrates the process of image reconstruction and latent acquisition in DDN. Each layer of DDN outputs K distinct images, here K = 3 , to approximate the distribution P ( X ) . The sampler then selects the image most similar to the target from these and feeds it into the next DDN layer. As the number of layers increases, the generated images become increasingly similar to the target. For generation tasks, the sampler is simply replaced with a random choice operation. Right: Shows the tree-structured representation space of DDN's latent variables. Each sample can be mapped to a leaf node on this tree. I find the method novel and elegant. The novelty is very strong, and this should…from discrete-distribution-networks.github.io
In the maker’s words, at launch
I invented Discrete Distribution Networks, a novel generative model with simple principles and unique properties, and the paper has been accepted to ICLR2025! Modeling data distribution is challenging; DDN adopts a simple yet fundamentally different approach compared to mainstream generative models (Diffusion, GAN…
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Discussions: Hacker News (63 points, 8 comments), Reddit r/programming (312 points, 37 comments) Translations: Arabic, French, Spanish Update: Part 2 is now live: A Visual And Interactive Look at Basic Neural Network Math Motivation I’m not a machine learning expert. I’m a software engineer by train
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