Brain Regions Engaged by Part- and Whole-task Performance in a Video Game: A Model-based Test of the Decomposition Hypothesis. - John R. Anderson; Daniel Bothell; Jon M. Fincham; Abraham R. Anderson; Ben Poole; Yulin Qin (J. Cogn. Neurosci., 2011)

An adaptive low dimensional quasi-Newton sum of functions optimizer. - Jascha Sohl-Dickstein; Ben Poole; Surya Ganguli (CoRR, 2013)

Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods. - Jascha Sohl-Dickstein; Ben Poole; Surya Ganguli (ICML, 2014)

Analyzing noise in autoencoders and deep networks. - Ben Poole; Jascha Sohl-Dickstein; Surya Ganguli (CoRR, 2014)

The Fast Bilateral Solver. - Jonathan T. Barron; Ben Poole (ECCV (3), 2016)

Exponential expressivity in deep neural networks through transient chaos. - Ben Poole; Subhaneil Lahiri; Maithra Raghu; Jascha Sohl-Dickstein; Surya Ganguli (NIPS, 2016)

Improved generator objectives for GANs. - Ben Poole; Alexander A. Alemi; Jascha Sohl-Dickstein; Anelia Angelova (CoRR, 2016)

Survey of Expressivity in Deep Neural Networks. - Maithra Raghu; Ben Poole; Jon M. Kleinberg; Surya Ganguli; Jascha Sohl-Dickstein (CoRR, 2016)

Adversarially Learned Inference. - Vincent Dumoulin; Ishmael Belghazi; Ben Poole; Alex Lamb; Martín Arjovsky; Olivier Mastropietro; Aaron C. Courville (ICLR (Poster), 2017)

Categorical Reparameterization with Gumbel-Softmax. - Eric Jang; Shixiang Gu; Ben Poole (ICLR (Poster), 2017)

Unrolled Generative Adversarial Networks. - Luke Metz; Ben Poole; David Pfau; Jascha Sohl-Dickstein (ICLR (Poster), 2017)

Intelligent synapses for multi-task and transfer learning. - Ben Poole; Friedemann Zenke; Surya Ganguli (ICLR (Workshop), 2017)

On the Expressive Power of Deep Neural Networks. - Maithra Raghu; Ben Poole; Jon M. Kleinberg; Surya Ganguli; Jascha Sohl-Dickstein (ICML, 2017)

Continual Learning Through Synaptic Intelligence. - Friedemann Zenke; Ben Poole; Surya Ganguli (ICML, 2017)

Improved multitask learning through synaptic intelligence. - Friedemann Zenke; Ben Poole; Surya Ganguli (CoRR, 2017)

An Information-Theoretic Analysis of Deep Latent-Variable Models. - Alexander A. Alemi; Ben Poole; Ian Fischer; Joshua V. Dillon; Rif A. Saurous; Kevin Murphy 002 (CoRR, 2017)

Fixing a Broken ELBO. - Alexander A. Alemi; Ben Poole; Ian Fischer; Joshua V. Dillon; Rif A. Saurous; Kevin Murphy 002 (ICML, 2018)

Preventing Posterior Collapse with delta-VAEs. - Ali Razavi; Aäron van den Oord; Ben Poole; Oriol Vinyals (ICLR (Poster), 2019)

On Variational Bounds of Mutual Information. - Ben Poole; Sherjil Ozair; Aäron van den Oord; Alexander A. Alemi; George Tucker (ICML, 2019)

Discrete Flows: Invertible Generative Models of Discrete Data. - Dustin Tran; Keyon Vafa; Kumar Krishna Agrawal; Laurent Dinh; Ben Poole (NeurIPS, 2019)

Improving Robustness Without Sacrificing Accuracy with Patch Gaussian Augmentation. - Raphael Gontijo Lopes; Dong Yin; Ben Poole; Justin Gilmer; Ekin D. Cubuk (CoRR, 2019)

On Predictive Information Sub-optimality of RNNs. - Zhe Dong; Deniz Oktay; Ben Poole; Alexander A. Alemi (CoRR, 2019)

Regularized Autoencoders via Relaxed Injective Probability Flow. - Abhishek Kumar; Ben Poole; Kevin Murphy 002 (AISTATS, 2020)

Weakly Supervised Disentanglement with Guarantees. - Rui Shu; Yining Chen; Abhishek Kumar; Stefano Ermon; Ben Poole (ICLR, 2020)

On Implicit Regularization in β-VAEs. - Abhishek Kumar; Ben Poole (ICML, 2020)

Weakly-Supervised Disentanglement Without Compromises. - Francesco Locatello; Ben Poole; Gunnar Rätsch; Bernhard Schölkopf; Olivier Bachem; Michael Tschannen (ICML, 2020)

What Makes for Good Views for Contrastive Learning? - Yonglong Tian; Chen Sun 002; Ben Poole; Dilip Krishnan; Cordelia Schmid; Phillip Isola (NeurIPS, 2020)

Using a thousand optimization tasks to learn hyperparameter search strategies. - Luke Metz; Niru Maheswaranathan; Ruoxi Sun 002; C. Daniel Freeman; Ben Poole; Jascha Sohl-Dickstein (CoRR, 2020)

Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves. - Luke Metz; Niru Maheswaranathan; C. Daniel Freeman; Ben Poole; Jascha Sohl-Dickstein (CoRR, 2020)

Non-saturating GAN training as divergence minimization. - Matt Shannon; Ben Poole; Soroosh Mariooryad; Tom Bagby; Eric Battenberg; David Kao; Daisy Stanton; R. J. Skerry-Ryan (CoRR, 2020)

VIB is Half Bayes. - Alexander A. Alemi; Warren R. Morningstar; Ben Poole; Ian Fischer; Joshua V. Dillon (CoRR, 2020)

Score-Based Generative Modeling through Stochastic Differential Equations. - Yang Song 011; Jascha Sohl-Dickstein; Diederik P. Kingma; Abhishek Kumar; Stefano Ermon; Ben Poole (ICLR, 2021)

Learning Energy-Based Models by Diffusion Recovery Likelihood. - Ruiqi Gao; Yang Song 011; Ben Poole; Ying Nian Wu; Diederik P. Kingma (ICLR, 2021)

On Density Estimation with Diffusion Models. - Diederik P. Kingma; Tim Salimans; Ben Poole; Jonathan Ho (NeurIPS, 2021)

Variational Diffusion Models. - Diederik P. Kingma; Tim Salimans; Ben Poole; Jonathan Ho (CoRR, 2021)

Zero-Shot Text-Guided Object Generation with Dream Fields. - Ajay Jain; Ben Mildenhall; Jonathan T. Barron; Pieter Abbeel; Ben Poole (CVPR, 2022)

Autoregressive Diffusion Models. - Emiel Hoogeboom; Alexey A. Gritsenko; Jasmijn Bastings; Ben Poole; Rianne van den Berg; Tim Salimans (ICLR, 2022)

Imagen Video: High Definition Video Generation with Diffusion Models. - Jonathan Ho; William Chan; Chitwan Saharia; Jay Whang; Ruiqi Gao; Alexey A. Gritsenko; Diederik P. Kingma; Ben Poole; Mohammad Norouzi 002; David J. Fleet; Tim Salimans (CoRR, 2022)

VeLO: Training Versatile Learned Optimizers by Scaling Up. - Luke Metz; James Harrison; C. Daniel Freeman; Amil Merchant; Lucas Beyer; James Bradbury; Naman Agrawal; Ben Poole; Igor Mordatch; Adam Roberts; Jascha Sohl-Dickstein (CoRR, 2022)

DreamBooth3D: Subject-Driven Text-to-3D Generation. - 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 (ICCV, 2023)

DreamFusion: Text-to-3D using 2D Diffusion. - Ben Poole; Ajay Jain; Jonathan T. Barron; Ben Mildenhall (ICLR, 2023)

Diffusion Self-Guidance for Controllable Image Generation. - Dave Epstein; Allan Jabri; Ben Poole; Alexei A. Efros; Aleksander Holynski (NeurIPS, 2023)

Learning a Diffusion Prior for NeRFs. - Guandao Yang; Abhijit Kundu; Leonidas J. Guibas; Jonathan T. Barron; Ben Poole (CoRR, 2023)

Variational Prediction. - Alexander A. Alemi; Ben Poole (CoRR, 2023)

Inpaint3D: 3D Scene Content Generation using 2D Inpainting Diffusion. - Kira Prabhu; Jane Wu; Lynn Tsai; Peter Hedman; Dan B. Goldman; Ben Poole; Michael Broxton (CoRR, 2023)

Video Interpolation with Diffusion Models. - Siddhant Jain; Daniel Watson; Eric Tabellion; Aleksander Holynski; Ben Poole; Janne Kontkanen (CVPR, 2024)

ReconFusion: 3D Reconstruction with Diffusion Priors. - Rundi Wu; Ben Mildenhall; Philipp Henzler; Keunhong Park; Ruiqi Gao; Daniel Watson; Pratul P. Srinivasan; Dor Verbin; Jonathan T. Barron; Ben Poole; Aleksander Holynski (CVPR, 2024)

Disentangled 3D Scene Generation with Layout Learning. - Dave Epstein; Ben Poole; Ben Mildenhall; Alexei A. Efros; Aleksander Holynski (ICML, 2024)

CAT3D: Create Anything in 3D with Multi-View Diffusion Models. - Ruiqi Gao; Aleksander Holynski; Philipp Henzler; Arthur Brussee; Ricardo Martin-Brualla; Pratul P. Srinivasan; Jonathan T. Barron; Ben Poole (NeurIPS, 2024)

EM Distillation for One-step Diffusion Models. - Sirui Xie; Zhisheng Xiao; Diederik P. Kingma; Tingbo Hou; Ying Nian Wu; Kevin P. Murphy; Tim Salimans; Ben Poole; Ruiqi Gao (NeurIPS, 2024)

SimVS: Simulating World Inconsistencies for Robust View Synthesis. - Alex Trevithick; Roni Paiss; Philipp Henzler; Dor Verbin; Rundi Wu; Hadi Alzayer; Ruiqi Gao; Ben Poole; Jonathan T. Barron; Aleksander Holynski; Ravi Ramamoorthi; Pratul P. Srinivasan (CVPR, 2025)

CAT4D: Create Anything in 4D with Multi-View Video Diffusion Models. - Rundi Wu; Ruiqi Gao; Ben Poole; Alex Trevithick; Changxi Zheng; Jonathan T. Barron; Aleksander Holynski (CVPR, 2025)

Masks make discriminative models great again! - Tianshi Cao; Marie-Julie Rakotosaona; Ben Poole; Federico Tombari; Michael Niemeyer (CoRR, 2025)