16.2k citations · 16.2k across the 5 of their papers we have counts for
5 papers
One-Step Diffusion Distillation via Deep Equilibrium Models
Zhengyang Geng, Ashwini Pokle, J. Zico Kolter
Diffusion models excel at producing high-quality samples but naively require hundreds of iterations, prompting multiple attempts to distill the generation process into a faster net…
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke, Sam Gross, Francisco Massa +18
Deep learning frameworks have often focused on either usability or speed, but not both. PyTorch is a machine learning library that shows that these two goals are in fact compatible…
Training Millions of Personalized Dialogue Agents
Pierre-Emmanuel Mazaré, Samuel Humeau, Martin Raison +1
Current dialogue systems are not very engaging for users, especially when trained end-to-end without relying on proactive reengaging scripted strategies. Zhang et al. (2018) showed…
Weaver: Deep Co-Encoding of Questions and Documents for Machine Reading
Martin Raison, Pierre-Emmanuel Mazaré, Rajarshi Das +1
This paper aims at improving how machines can answer questions directly from text, with the focus of having models that can answer correctly multiple types of questions and from va…
Ringo: Interactive Graph Analytics on Big-Memory Machines
Yonathan Perez, Rok Sosic, Arijit Banerjee +4
We present Ringo, a system for analysis of large graphs. Graphs provide a way to represent and analyze systems of interacting objects (people, proteins, webpages) with edges betwee…