Ben Poole

CoRR, 2024

Disentangled 3D Scene Generation with Layout Learning.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

ReconFusion: 3D Reconstruction with Diffusion Priors.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Video Interpolation with Diffusion Models.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

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

[BibT_eX]

[DOI]

CoRR, 2023

Variational Prediction.

[BibT_eX]

[DOI]

Alexander A. Alemi

CoRR, 2023

Learning a Diffusion Prior for NeRFs.

[BibT_eX]

[DOI]

CoRR, 2023

Diffusion Self-Guidance for Controllable Image Generation.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

DreamBooth3D: Subject-Driven Text-to-3D Generation.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

VeLO: Training Versatile Learned Optimizers by Scaling Up.

[BibT_eX]

[DOI]

CoRR, 2022

Imagen Video: High Definition Video Generation with Diffusion Models.

[BibT_eX]

[DOI]

CoRR, 2022

Autoregressive Diffusion Models.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Zero-Shot Text-Guided Object Generation with Dream Fields.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Variational Diffusion Models.

[BibT_eX]

[DOI]

CoRR, 2021

On Density Estimation with Diffusion Models.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

Score-Based Generative Modeling through Stochastic Differential Equations.

[BibT_eX]

[DOI]

Yang Song

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

VIB is Half Bayes.

[BibT_eX]

[DOI]

Alexander A. Alemi

Warren R. Morningstar

Ian Fischer

Joshua V. Dillon

CoRR, 2020

Non-saturating GAN training as divergence minimization.

[BibT_eX]

[DOI]

CoRR, 2020

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

[BibT_eX]

[DOI]

CoRR, 2020

Using a thousand optimization tasks to learn hyperparameter search strategies.

[BibT_eX]

[DOI]

CoRR, 2020

What Makes for Good Views for Contrastive Learning?

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Weakly-Supervised Disentanglement Without Compromises.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

On Implicit Regularization in β-VAEs.

[BibT_eX]

[DOI]

Abhishek Kumar

Proceedings of the 37th International Conference on Machine Learning, 2020

Weakly Supervised Disentanglement with Guarantees.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Regularized Autoencoders via Relaxed Injective Probability Flow.

[BibT_eX]

[DOI]

Abhishek Kumar

Kevin Murphy

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

On Predictive Information Sub-optimality of RNNs.

[BibT_eX]

[DOI]

CoRR, 2019

Improving Robustness Without Sacrificing Accuracy with Patch Gaussian Augmentation.

[BibT_eX]

[DOI]

Raphael Gontijo Lopes

CoRR, 2019

Discrete Flows: Invertible Generative Models of Discrete Data.

[BibT_eX]

[DOI]

Dustin Tran

Keyon Vafa

Kumar Krishna Agrawal

Laurent Dinh

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.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Preventing Posterior Collapse with delta-VAEs.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Fixing a Broken ELBO.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

An Information-Theoretic Analysis of Deep Latent-Variable Models.

[BibT_eX]

[DOI]

CoRR, 2017

Improved multitask learning through synaptic intelligence.

[BibT_eX]

[DOI]

Friedemann Zenke

CoRR, 2017

Continual Learning Through Synaptic Intelligence.

[BibT_eX]

[DOI]

Friedemann Zenke

Proceedings of the 34th International Conference on Machine Learning, 2017

On the Expressive Power of Deep Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 34th International Conference on Machine Learning, 2017

Intelligent synapses for multi-task and transfer learning.

[BibT_eX]

[DOI]

Friedemann Zenke

Proceedings of the 5th International Conference on Learning Representations, 2017

Unrolled Generative Adversarial Networks.

[BibT_eX]

[DOI]

Luke Metz

David Pfau

Proceedings of the 5th International Conference on Learning Representations, 2017

Categorical Reparameterization with Gumbel-Softmax.

[BibT_eX]

[DOI]

Eric Jang

Shixiang Gu

Proceedings of the 5th International Conference on Learning Representations, 2017

Adversarially Learned Inference.

[BibT_eX]

[DOI]

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Survey of Expressivity in Deep Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2016

Improved generator objectives for GANs.

[BibT_eX]

[DOI]

Alexander A. Alemi

Anelia Angelova

CoRR, 2016

Exponential expressivity in deep neural networks through transient chaos.

[BibT_eX]

[DOI]

Subhaneil Lahiri

Maithra Raghu

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

The Fast Bilateral Solver.

[BibT_eX]

[DOI]

Jonathan T. Barron

Proceedings of the Computer Vision - ECCV 2016, 2016

2014

Analyzing noise in autoencoders and deep networks.

[BibT_eX]

[DOI]

CoRR, 2014

Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods.

[BibT_eX]

[DOI]

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

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

[BibT_eX]

[DOI]