| Latent Variables on Spheres for Sampling and Inference | Sep 25, 2019 | Variational Inference | —Unverified | 0 |
| Gaussian Process Meta-Representations Of Neural Networks | Sep 25, 2019 | Active LearningBayesian Inference | —Unverified | 0 |
| BasisVAE: Orthogonal Latent Space for Deep Disentangled Representation | Sep 25, 2019 | DisentanglementVariational Inference | —Unverified | 0 |
| On PAC-Bayes Bounds for Deep Neural Networks using the Loss Curvature | Sep 25, 2019 | Variational Inference | —Unverified | 0 |
| On the Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks | Sep 25, 2019 | Bayesian InferenceVariational Inference | —Unverified | 0 |
| LIA: Latently Invertible Autoencoder with Adversarial Learning | Sep 25, 2019 | DecoderGenerative Adversarial Network | —Unverified | 0 |
| An Information Theoretic Approach to Distributed Representation Learning | Sep 25, 2019 | Representation LearningVariational Inference | —Unverified | 0 |
| Benefits of Overparameterization in Single-Layer Latent Variable Generative Models | Sep 25, 2019 | Variational Inference | —Unverified | 0 |
| Shallow VAEs with RealNVP Prior Can Perform as Well as Deep Hierarchical VAEs | Sep 25, 2019 | Variational Inference | —Unverified | 0 |
| Refining the variational posterior through iterative optimization | Sep 25, 2019 | Bayesian InferenceVariational Inference | —Unverified | 0 |
