3k citations · 10.2k across the 21 of their papers we have counts for
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Improved Techniques for Training Consistency Models
Yang Song, Prafulla Dhariwal
Consistency models are a nascent family of generative models that can sample high quality data in one step without the need for adversarial training. Current consistency models ach…
Consistency Models
Yang Song, Prafulla Dhariwal, Mark Chen +1
Diffusion models have significantly advanced the fields of image, audio, and video generation, but they depend on an iterative sampling process that causes slow generation. To over…
Diffusion Models Beat GANs on Image Synthesis
Prafulla Dhariwal, Alex Nichol
We show that diffusion models can achieve image sample quality superior to the current state-of-the-art generative models. We achieve this on unconditional image synthesis by findi…
Improved Denoising Diffusion Probabilistic Models
Alex Nichol, Prafulla Dhariwal
Denoising diffusion probabilistic models (DDPM) are a class of generative models which have recently been shown to produce excellent samples. We show that with a few simple modific…
Scaling Laws for Autoregressive Generative Modeling
Tom Henighan, Jared Kaplan, Mor Katz +16
We identify empirical scaling laws for the cross-entropy loss in four domains: generative image modeling, video modeling, multimodal imagetext models, and mathemat…
GamePad: A Learning Environment for Theorem Proving
Daniel Huang, Prafulla Dhariwal, Dawn Song +1
In this paper, we introduce a system called GamePad that can be used to explore the application of machine learning methods to theorem proving in the Coq proof assistant. Interacti…
Proximal Policy Optimization Algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal +2
We propose a new family of policy gradient methods for reinforcement learning, which alternate between sampling data through interaction with the environment, and optimizing a "sur…
Parameter Space Noise for Exploration
Matthias Plappert, Rein Houthooft, Prafulla Dhariwal +6
Deep reinforcement learning (RL) methods generally engage in exploratory behavior through noise injection in the action space. An alternative is to add noise directly to the agent'…
Variational Lossy Autoencoder
Xi Chen, Diederik P. Kingma, Tim Salimans +5
Representation learning seeks to expose certain aspects of observed data in a learned representation that's amenable to downstream tasks like classification. For instance, a good r…