DDPM
Denoising Diffusion Probabilistic Models (DDPM) are a class of generative model introduced by Jonathan Ho, Ajay Jain, and Pieter Abbeel of UC Berkeley in their June 2020 paper "Denoising Diffusion…
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Showing 1-14 of 14 articles
Diffusion model
A diffusion model is a generative model that learns to transform samples from a simple reference distribution into samples resembling a data distribution by reversing a gradual corruption process.
Discriminator
A discriminator is the neural network in a generative adversarial network (GAN) that is trained to tell real data apart from data produced by the generator
Generative AI
Generative AI is a class of artificial intelligence systems that produces new data instances, such as text, software code, images, audio, video, molecular structures, or other representations, by learning…
Generative Model
A generative model is a class of statistical and machine learning model that learns the joint probability distribution P(X) of the observed data, or the joint distribution P(X, Y) of inputs and labels
Generative adversarial network
Generative adversarial networks (GANs) are a family of generative models trained through competition between two learned functions.
Generator
A generator is a neural network within a generative adversarial network (GAN) that learns to produce synthetic data samples from random noise.
Latent Space
A latent space is the vector space a machine learning model maps its inputs into, where each input becomes a point (a latent vector or latent code) and the geometry of the space carries information the raw…
Minimax Loss
Minimax loss is a loss function rooted in game theory and decision theory that measures the worst-case performance of a strategy, algorithm, or model.
Natural language generation
Natural language generation (NLG) is the subfield of natural language processing and artificial intelligence concerned with building systems that produce understandable text in English or other human…
Stefano Ermon
Stefano Ermon is an Italian computer scientist and an associate professor of computer science at Stanford University, best known for foundational work on score-based generative models
Training AI to Paint with Code
Training AI to Paint with Code is an experimental AI art project published by designer and researcher Surya Narreddi in March 2026.
Wasserstein Loss
Wasserstein loss is a loss function for training generative models that measures the distance between two probability distributions as the Wasserstein-1 distance
Z.ai
Z.ai is the international brand of the Chinese artificial intelligence company Zhipu AI (智谱AI), a 2019 spinout from Tsinghua University that builds the open-weight General Language Model (GLM) family and…