Ben Poole

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 67

Top Topics

High Definition Video

Weakly Supervised

Diffusion Models

Top Venues

Publications

Sirui Xie, Zhisheng Xiao, Diederik P. Kingma, Tingbo Hou, Ying Nian Wu, Kevin Patrick Murphy, Tim Salimans, Ben Poole, Ruiqi Gao
EM Distillation for One-step Diffusion Models. CoRR (2024)
Siddhant Jain, Daniel Watson, Eric Tabellion, Aleksander Holynski, Ben Poole, Janne Kontkanen
Video Interpolation with Diffusion Models. CoRR (2024)
Ruiqi Gao, Aleksander Holynski, Philipp Henzler, Arthur Brussee, Ricardo Martin-Brualla, Pratul P. Srinivasan, Jonathan T. Barron, Ben Poole
CAT3D: Create Anything in 3D with Multi-View Diffusion Models. CoRR (2024)
Dave Epstein, Ben Poole, Ben Mildenhall, Alexei A. Efros, Aleksander Holynski
Disentangled 3D Scene Generation with Layout Learning. CoRR (2024)
Alexander A. Alemi, Ben Poole
Variational Prediction. CoRR (2023)
Ben Poole, Ajay Jain, Jonathan T. Barron, Ben Mildenhall
DreamFusion: Text-to-3D using 2D Diffusion. ICLR (2023)
Dave Epstein, Allan Jabri, Ben Poole, Alexei A. Efros, Aleksander Holynski
Diffusion Self-Guidance for Controllable Image Generation. CoRR (2023)
Rundi Wu, Ben Mildenhall, Philipp Henzler, Keunhong Park, Ruiqi Gao, Daniel Watson, Pratul P. Srinivasan, Dor Verbin, Jonathan T. Barron, Ben Poole, Aleksander Holynski
ReconFusion: 3D Reconstruction with Diffusion Priors. CoRR (2023)
Dave Epstein, Allan Jabri, Ben Poole, Alexei A. Efros, Aleksander Holynski
Diffusion Self-Guidance for Controllable Image Generation. NeurIPS (2023)
Kira Prabhu, Jane Wu, Lynn Tsai, Peter Hedman, Dan B. Goldman, Ben Poole, Michael Broxton
Inpaint3D: 3D Scene Content Generation using 2D Inpainting Diffusion. CoRR (2023)
Amit Raj, Srinivas Kaza, Ben Poole, Michael Niemeyer, Nataniel Ruiz, Ben Mildenhall, Shiran Zada, Kfir Aberman, Michael Rubinstein, Jonathan T. Barron, Yuanzhen Li, Varun Jampani
DreamBooth3D: Subject-Driven Text-to-3D Generation. ICCV (2023)
Guandao Yang, Abhijit Kundu, Leonidas J. Guibas, Jonathan T. Barron, Ben Poole
Learning a Diffusion Prior for NeRFs. CoRR (2023)
Amit Raj, Srinivas Kaza, Ben Poole, Michael Niemeyer, Nataniel Ruiz, Ben Mildenhall, Shiran Zada, Kfir Aberman, Michael Rubinstein, Jonathan T. Barron, Yuanzhen Li, Varun Jampani
DreamBooth3D: Subject-Driven Text-to-3D Generation. CoRR (2023)
Emiel Hoogeboom, Alexey A. Gritsenko, Jasmijn Bastings, Ben Poole, Rianne van den Berg, Tim Salimans
Autoregressive Diffusion Models. ICLR (2022)
Luke Metz, James Harrison, C. Daniel Freeman, Amil Merchant, Lucas Beyer, James Bradbury, Naman Agrawal, Ben Poole, Igor Mordatch, Adam Roberts, Jascha Sohl-Dickstein
VeLO: Training Versatile Learned Optimizers by Scaling Up. CoRR (2022)
Ben Poole, Ajay Jain, Jonathan T. Barron, Ben Mildenhall
DreamFusion: Text-to-3D using 2D Diffusion. CoRR (2022)
Jonathan Ho, William Chan, Chitwan Saharia, Jay Whang, Ruiqi Gao, Alexey A. Gritsenko, Diederik P. Kingma, Ben Poole, Mohammad Norouzi, David J. Fleet, Tim Salimans
Imagen Video: High Definition Video Generation with Diffusion Models. CoRR (2022)
Ajay Jain, Ben Mildenhall, Jonathan T. Barron, Pieter Abbeel, Ben Poole
Zero-Shot Text-Guided Object Generation with Dream Fields. CVPR (2022)
Ajay Jain, Ben Mildenhall, Jonathan T. Barron, Pieter Abbeel, Ben Poole
Zero-Shot Text-Guided Object Generation with Dream Fields. CoRR (2021)
Diederik P. Kingma, Tim Salimans, Ben Poole, Jonathan Ho
Variational Diffusion Models. CoRR (2021)
Emiel Hoogeboom, Alexey A. Gritsenko, Jasmijn Bastings, Ben Poole, Rianne van den Berg, Tim Salimans
Autoregressive Diffusion Models. CoRR (2021)
Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, Diederik P. Kingma
Learning Energy-Based Models by Diffusion Recovery Likelihood. ICLR (2021)
Diederik P. Kingma, Tim Salimans, Ben Poole, Jonathan Ho
On Density Estimation with Diffusion Models. NeurIPS (2021)
Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole
Score-Based Generative Modeling through Stochastic Differential Equations. ICLR (2021)
Matt Shannon, Ben Poole, Soroosh Mariooryad, Tom Bagby, Eric Battenberg, David Kao, Daisy Stanton, R. J. Skerry-Ryan
Non-saturating GAN training as divergence minimization. CoRR (2020)
Abhishek Kumar, Ben Poole
On Implicit Regularization in β-VAEs. ICML (2020)
Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole
Score-Based Generative Modeling through Stochastic Differential Equations. CoRR (2020)
Abhishek Kumar, Ben Poole, Kevin Murphy
Regularized Autoencoders via Relaxed Injective Probability Flow. CoRR (2020)
Francesco Locatello, Ben Poole, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem, Michael Tschannen
Weakly-Supervised Disentanglement Without Compromises. ICML (2020)
Luke Metz, Niru Maheswaranathan, C. Daniel Freeman, Ben Poole, Jascha Sohl-Dickstein
Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves. CoRR (2020)
Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, Phillip Isola
What Makes for Good Views for Contrastive Learning? NeurIPS (2020)
Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, Diederik P. Kingma
Learning Energy-Based Models by Diffusion Recovery Likelihood. CoRR (2020)
Abhishek Kumar, Ben Poole, Kevin Murphy
Regularized Autoencoders via Relaxed Injective Probability Flow. AISTATS (2020)
Luke Metz, Niru Maheswaranathan, Ruoxi Sun, C. Daniel Freeman, Ben Poole, Jascha Sohl-Dickstein
Using a thousand optimization tasks to learn hyperparameter search strategies. CoRR (2020)
Abhishek Kumar, Ben Poole
On Implicit Regularization in β-VAEs. CoRR (2020)
Francesco Locatello, Ben Poole, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem, Michael Tschannen
Weakly-Supervised Disentanglement Without Compromises. CoRR (2020)
Rui Shu, Yining Chen, Abhishek Kumar, Stefano Ermon, Ben Poole
Weakly Supervised Disentanglement with Guarantees. ICLR (2020)
Alexander A. Alemi, Warren R. Morningstar, Ben Poole, Ian Fischer, Joshua V. Dillon
VIB is Half Bayes. CoRR (2020)
Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, Phillip Isola
What makes for good views for contrastive learning. CoRR (2020)
Zhe Dong, Deniz Oktay, Ben Poole, Alexander A. Alemi
On Predictive Information Sub-optimality of RNNs. CoRR (2019)
Ali Razavi, Aäron van den Oord, Ben Poole, Oriol Vinyals
Preventing Posterior Collapse with delta-VAEs. ICLR (Poster) (2019)
Ali Razavi, Aäron van den Oord, Ben Poole, Oriol Vinyals
Preventing Posterior Collapse with delta-VAEs. CoRR (2019)
Rui Shu, Yining Chen, Abhishek Kumar, Stefano Ermon, Ben Poole
Weakly Supervised Disentanglement with Guarantees. CoRR (2019)
Dustin Tran, Keyon Vafa, Kumar Krishna Agrawal, Laurent Dinh, Ben Poole
Discrete Flows: Invertible Generative Models of Discrete Data. CoRR (2019)
Ben Poole, Sherjil Ozair, Aäron van den Oord, Alexander A. Alemi, George Tucker
On Variational Bounds of Mutual Information. CoRR (2019)
Dustin Tran, Keyon Vafa, Kumar Krishna Agrawal, Laurent Dinh, Ben Poole
Discrete Flows: Invertible Generative Models of Discrete Data. NeurIPS (2019)
Raphael Gontijo Lopes, Dong Yin, Ben Poole, Justin Gilmer, Ekin D. Cubuk
Improving Robustness Without Sacrificing Accuracy with Patch Gaussian Augmentation. CoRR (2019)
Dustin Tran, Keyon Vafa, Kumar Krishna Agrawal, Laurent Dinh, Ben Poole
Discrete Flows: Invertible Generative Models of Discrete Data. DGS@ICLR (2019)
Ben Poole, Sherjil Ozair, Aäron van den Oord, Alex Alemi, George Tucker
On Variational Bounds of Mutual Information. ICML (2019)
Alexander A. Alemi, Ben Poole, Ian Fischer, Joshua V. Dillon, Rif A. Saurous, Kevin Murphy
Fixing a Broken ELBO. ICML (2018)
Ben Poole, Friedemann Zenke, Surya Ganguli
Intelligent synapses for multi-task and transfer learning. ICLR (Workshop) (2017)
Maithra Raghu, Ben Poole, Jon M. Kleinberg, Surya Ganguli, Jascha Sohl-Dickstein
On the Expressive Power of Deep Neural Networks. ICML (2017)
Luke Metz, Ben Poole, David Pfau, Jascha Sohl-Dickstein
Unrolled Generative Adversarial Networks. ICLR (Poster) (2017)
Friedemann Zenke, Ben Poole, Surya Ganguli
Improved multitask learning through synaptic intelligence. CoRR (2017)
Eric Jang, Shixiang Gu, Ben Poole
Categorical Reparameterization with Gumbel-Softmax. ICLR (Poster) (2017)
Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martín Arjovsky, Olivier Mastropietro, Aaron C. Courville
Adversarially Learned Inference. ICLR (Poster) (2017)
Alexander A. Alemi, Ben Poole, Ian Fischer, Joshua V. Dillon, Rif A. Saurous, Kevin Murphy
An Information-Theoretic Analysis of Deep Latent-Variable Models. CoRR (2017)
Friedemann Zenke, Ben Poole, Surya Ganguli
Continual Learning Through Synaptic Intelligence. ICML (2017)
Ben Poole, Subhaneil Lahiri, Maithra Raghu, Jascha Sohl-Dickstein, Surya Ganguli
Exponential expressivity in deep neural networks through transient chaos. CoRR (2016)
Ben Poole, Subhaneil Lahiri, Maithra Raghu, Jascha Sohl-Dickstein, Surya Ganguli
Exponential expressivity in deep neural networks through transient chaos. NIPS (2016)
Eric Jang, Shixiang Gu, Ben Poole
Categorical Reparameterization with Gumbel-Softmax. CoRR (2016)
Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martín Arjovsky, Olivier Mastropietro, Aaron C. Courville
Adversarially Learned Inference. CoRR (2016)
Maithra Raghu, Ben Poole, Jon M. Kleinberg, Surya Ganguli, Jascha Sohl-Dickstein
On the expressive power of deep neural networks. CoRR (2016)
Luke Metz, Ben Poole, David Pfau, Jascha Sohl-Dickstein
Unrolled Generative Adversarial Networks. CoRR (2016)
Jonathan T. Barron, Ben Poole
The Fast Bilateral Solver. ECCV (3) (2016)
Ben Poole, Alexander A. Alemi, Jascha Sohl-Dickstein, Anelia Angelova
Improved generator objectives for GANs. CoRR (2016)
Maithra Raghu, Ben Poole, Jon M. Kleinberg, Surya Ganguli, Jascha Sohl-Dickstein
Survey of Expressivity in Deep Neural Networks. CoRR (2016)
Jonathan T. Barron, Ben Poole
The Fast Bilateral Solver. CoRR (2015)
Ben Poole, Jascha Sohl-Dickstein, Surya Ganguli
Analyzing noise in autoencoders and deep networks. CoRR (2014)
Jascha Sohl-Dickstein, Ben Poole, Surya Ganguli
Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods. ICML (2014)
Jascha Sohl-Dickstein, Ben Poole, Surya Ganguli
An adaptive low dimensional quasi-Newton sum of functions optimizer. CoRR (2013)
John R. Anderson, Daniel Bothell, Jon M. Fincham, Abraham R. Anderson, Ben Poole, Yulin Qin
Brain Regions Engaged by Part- and Whole-task Performance in a Video Game: A Model-based Test of the Decomposition Hypothesis. J. Cogn. Neurosci. 23 (12) (2011)