Ruben Villegas

Ruben Villegas

My main research focuses on generative modeling, self-supervised learning and multimodal learning in the video domain. I am interested in effectively incorporating the time dimension to learn more general representations towards the goal of compositional generalization.Visit my personal website for more details and publications.

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Phenaki: Variable length video generation from open domain textual descriptions
Ruben Villegas
Mohammad Babaeizadeh
Pieter-Jan Kindermans
Hernan Moraldo
Han Zhang
Mohammad Taghi Saffar
Santiago Castro
Julius Kunze
Dumitru Erhan
ICLR (2023)
High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks
Ruben Villegas
Arkanath Pathak
Harini Kannan
Dumitru Erhan
Quoc Le
Honglak Lee
NeurIPS (2019)
Unsupervised Learning of Object Structure and Dynamics from Videos
Matthias Minderer
Chen Sun
Ruben Villegas
Forrester Cole
Kevin Murphy
Honglak Lee
NeurIPS (2019)
Learning Latent Dynamics for Planning from Pixels
Danijar Hafner
Timothy Lillicrap
Ian Fischer
Ruben Villegas
David Ha
Honglak Lee
James Davidson
International Conference on Machine Learning (2019)
Hierarchical Long-term Video Prediction without Supervision
Nevan Wichers
Ruben Villegas
Dumitru Erhan
Honglak Lee
ICML (2018)
Learning to Generate Long-term Future via Hierarchical Prediction
Ruben Villegas
Jimei Yang
Yuliang Zou
Sungryull Sohn
Xunyu Lin
Honglak Lee
ICML (2017)
Decomposing Motion and Content for Natural Video Sequence Prediction
Ruben Villegas
Jimei Yang
Seunghoon Hong
Xunyu Lin
Honglak Lee
ICLR (2017)
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