Ben Poole

According to our database1, Ben Poole authored at least 47 papers between 2011 and 2024.

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Bibliography

2024
Disentangled 3D Scene Generation with Layout Learning.
CoRR, 2024

2023
Inpaint3D: 3D Scene Content Generation using 2D Inpainting Diffusion.
CoRR, 2023

ReconFusion: 3D Reconstruction with Diffusion Priors.
CoRR, 2023

Variational Prediction.
CoRR, 2023

Learning a Diffusion Prior for NeRFs.
CoRR, 2023

Diffusion Self-Guidance for Controllable Image Generation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

DreamFusion: Text-to-3D using 2D Diffusion.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

DreamBooth3D: Subject-Driven Text-to-3D Generation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
VeLO: Training Versatile Learned Optimizers by Scaling Up.
CoRR, 2022

Imagen Video: High Definition Video Generation with Diffusion Models.
CoRR, 2022

Autoregressive Diffusion Models.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Zero-Shot Text-Guided Object Generation with Dream Fields.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Variational Diffusion Models.
CoRR, 2021

On Density Estimation with Diffusion Models.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning Energy-Based Models by Diffusion Recovery Likelihood.
Proceedings of the 9th International Conference on Learning Representations, 2021

Score-Based Generative Modeling through Stochastic Differential Equations.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
VIB is Half Bayes.
CoRR, 2020

Non-saturating GAN training as divergence minimization.
CoRR, 2020

Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves.
CoRR, 2020

Using a thousand optimization tasks to learn hyperparameter search strategies.
CoRR, 2020

What Makes for Good Views for Contrastive Learning?
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Weakly-Supervised Disentanglement Without Compromises.
Proceedings of the 37th International Conference on Machine Learning, 2020

On Implicit Regularization in β-VAEs.
Proceedings of the 37th International Conference on Machine Learning, 2020

Weakly Supervised Disentanglement with Guarantees.
Proceedings of the 8th International Conference on Learning Representations, 2020

Regularized Autoencoders via Relaxed Injective Probability Flow.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
On Predictive Information Sub-optimality of RNNs.
CoRR, 2019

Improving Robustness Without Sacrificing Accuracy with Patch Gaussian Augmentation.
CoRR, 2019

Discrete Flows: Invertible Generative Models of Discrete Data.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

On Variational Bounds of Mutual Information.
Proceedings of the 36th International Conference on Machine Learning, 2019

Preventing Posterior Collapse with delta-VAEs.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Fixing a Broken ELBO.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
An Information-Theoretic Analysis of Deep Latent-Variable Models.
CoRR, 2017

Improved multitask learning through synaptic intelligence.
CoRR, 2017

Continual Learning Through Synaptic Intelligence.
Proceedings of the 34th International Conference on Machine Learning, 2017

On the Expressive Power of Deep Neural Networks.
Proceedings of the 34th International Conference on Machine Learning, 2017

Intelligent synapses for multi-task and transfer learning.
Proceedings of the 5th International Conference on Learning Representations, 2017

Unrolled Generative Adversarial Networks.
Proceedings of the 5th International Conference on Learning Representations, 2017

Categorical Reparameterization with Gumbel-Softmax.
Proceedings of the 5th International Conference on Learning Representations, 2017

Adversarially Learned Inference.
Proceedings of the 5th International Conference on Learning Representations, 2017

2016
Survey of Expressivity in Deep Neural Networks.
CoRR, 2016

Improved generator objectives for GANs.
CoRR, 2016

Exponential expressivity in deep neural networks through transient chaos.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

The Fast Bilateral Solver.
Proceedings of the Computer Vision - ECCV 2016, 2016

2014
Analyzing noise in autoencoders and deep networks.
CoRR, 2014

Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
An adaptive low dimensional quasi-Newton sum of functions optimizer.
CoRR, 2013

2011
Brain Regions Engaged by Part- and Whole-task Performance in a Video Game: A Model-based Test of the Decomposition Hypothesis.
J. Cogn. Neurosci., 2011


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