
Weakly Supervised Disentanglement with Guarantees
Learning disentangled representations that correspond to factors of vari...
10/22/2019 ∙ by Rui Shu, et al. ∙ 12 ∙ shareread it

On Variational Bounds of Mutual Information
Estimating and optimizing Mutual Information (MI) is core to many proble...
05/16/2019 ∙ by Ben Poole, et al. ∙ 8 ∙ shareread it

Discrete Flows: Invertible Generative Models of Discrete Data
While normalizing flows have led to significant advances in modeling hig...
05/24/2019 ∙ by Dustin Tran, et al. ∙ 6 ∙ shareread it

Preventing Posterior Collapse with deltaVAEs
Due to the phenomenon of "posterior collapse," current latent variable g...
01/10/2019 ∙ by Ali Razavi, et al. ∙ 4 ∙ shareread it

An InformationTheoretic Analysis of Deep LatentVariable Models
We present an informationtheoretic framework for understanding tradeof...
11/01/2017 ∙ by Alexander A. Alemi, et al. ∙ 0 ∙ shareread it

Survey of Expressivity in Deep Neural Networks
We survey results on neural network expressivity described in "On the Ex...
11/24/2016 ∙ by Maithra Raghu, et al. ∙ 0 ∙ shareread it

Analyzing noise in autoencoders and deep networks
Autoencoders have emerged as a useful framework for unsupervised learnin...
06/06/2014 ∙ by Ben Poole, et al. ∙ 0 ∙ shareread it

Continual Learning Through Synaptic Intelligence
While deep learning has led to remarkable advances across diverse applic...
03/13/2017 ∙ by Friedemann Zenke, et al. ∙ 0 ∙ shareread it

Unrolled Generative Adversarial Networks
We introduce a method to stabilize Generative Adversarial Networks (GANs...
11/07/2016 ∙ by Luke Metz, et al. ∙ 0 ∙ shareread it

Categorical Reparameterization with GumbelSoftmax
Categorical variables are a natural choice for representing discrete str...
11/03/2016 ∙ by Eric Jang, et al. ∙ 0 ∙ shareread it

Exponential expressivity in deep neural networks through transient chaos
We combine Riemannian geometry with the mean field theory of high dimens...
06/16/2016 ∙ by Ben Poole, et al. ∙ 0 ∙ shareread it

On the Expressive Power of Deep Neural Networks
We propose a new approach to the problem of neural network expressivity,...
06/16/2016 ∙ by Maithra Raghu, et al. ∙ 0 ∙ shareread it

Adversarially Learned Inference
We introduce the adversarially learned inference (ALI) model, which join...
06/02/2016 ∙ by Vincent Dumoulin, et al. ∙ 0 ∙ shareread it

The Fast Bilateral Solver
We present the bilateral solver, a novel algorithm for edgeaware smooth...
11/10/2015 ∙ by Jonathan T. Barron, et al. ∙ 0 ∙ shareread it

Improving Robustness Without Sacrificing Accuracy with Patch Gaussian Augmentation
Deploying machine learning systems in the real world requires both high ...
06/06/2019 ∙ by Raphael Gontijo Lopes, et al. ∙ 0 ∙ shareread it

On Predictive Information Suboptimality of RNNs
Certain biological neurons demonstrate a remarkable capability to optima...
10/21/2019 ∙ by Zhe Dong, et al. ∙ 0 ∙ shareread it
Ben Poole
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